“Factors influencing the export performance of European
SMEs”
-The case of France and the UK-
H.F.M Stutvoet
Business Student
S1508164
University of Groningen
Faculty of Management and Organization
Msc. International Business and Management
Landleven 5
9747 AD Groningen
“Factors influencing the export performance of European
SMEs”
-The case of France and the UK-
ABSTRACT1
The aim of this study is to seek out the effects of the internal and external influences on export performance between SMEs in the automotive industry from France and the UK. The results show that firm size and ownership type have a significant relation with the French SMEs, but not with the UK SMEs. Furthermore country culture, country government and country size, show differences between France and the UK. Based on the low uncertainty avoidance index and index of economical freedom of the UK the tests show that the UK has a better export performance than France. Based on the high power distance index and lower GDP of France the tests show that France has a better performance than the UK. Combined with other literature found, it can be assumed that the differences between the countries are caused by the fact that the development of the UK automotive industry is staying behind the French due to the lack of investments made into HRM and R&D, which are a vital component in staying competitive in this industry. Furthermore, the UK automotive exporters have suffered from the high exchange rate of the pound sterling.
TABLE OF CONTENTS
1. INTRODUCTION 4
1.1 Problem Indication and Main Research Question 5 1.2 Significance of the Research 6
1.3 Research Outline 7
2. THEORETICAL BACKGROUND 8
2.1 Automotive Industry 8
2.1.1 Automotive statistics and trends 8
2.2 Hypotheses 14 2.2.1 Firm size 15 2.2.2 Ownership type 15 2.2.3 Country culture 16 2.2.4 Country’s government 19 2.2.5 Country size 19 3. METHODOLOGY 20 3.1 Selection Process 20 3.2 Operationalization 22 3.2.1 Firm size 22 3.2.2 Ownership 22 3.2.3 Country culture 22 3.2.4 Country’s government 23 3.2.5 Country size 23 3.2.6 Export performance 23 3.3 Type of Study 23 3.4 Tests 24 3.5 Sample Size 24 3.6 Conceptual Model 25 4. RESULTS 26 5. DISCUSSION 29
6. CONCLUSIONS AND LIMITATIONS 33
REFERENCES 35
APPENDIXES 43
LIST OF FIGURS
Figure 2.1.1.6: French subsidiaries of foreign automotive companies 13
Figure 3.6: Conceptual model 25
LIST OF TABLES
Table 2.1.1.1: Number of Companies from the UK Automotive Industry 9
Table 2.1.1.2: Number of Employees in the UK Automotive industry 9
Table 2.1.1.3: Trade Balance of the UK Automotive Industry 9
Table 2.1.1.4: Vehicle Production Capacity Data of the UK and French Automotive Industry 11
Table 2.1.1.5: Productivity in GDP per Employee per Hour in USD in
the UK and French Automotive Industry. 12
Table 2.1.1.7: FDI in the Automotive Industry 13
Table 2.2.3.1: Relative export and the UAI, 2005 17
Table 2.2.3.2: Relative export and PDI, 2005 18
1. INTRODUCTION
“EXPORT PERFORMANCE IS ONE OF THE MOST WIDELY RESEARCHED BUT LEAST UNDERSTOOD AND MOST CONTENTIOUS AREAS OF
INTERNATIONAL MARKETING. TO SOME EXTEND, THIS PROBLEM CAN BE ASCRIBED TO DIFFICULTIES IN CONCEPUALIZING, OPERATIONALIZATION,
AND MEARURING THE EXPORT PERFORMANCE CONSTRUCT, OFTEN LEADING TO INCONSISTENT AND CONFLICTING RESULTS.”
Katsikeas (1994)
The article of Johanson and Wiedersheim-Paul (1975) showed the internationalization process of four Swedish companies. Based on this study the Uppsala model describes four distinct stages in which a firm becomes more international involved. However, recent discussions shed a new light on this model and other stage modes. “Born global” companies show a different kind of
internationalization. These firms adopt an international or even global approach right from their birth or very shortly thereafter. This is considered as being in strong opposition to the traditional models of internationalization (Masen and Servais, 1997). This new kind of organization shows that it is possible to succeed in world markets without establishing a domestic base. These firms achieve an export of 20% of their total sales within two years (McKinsey and Co,
1993).Therefore, factors influencing the internationalisation of companies are changing and export plays a very important part in this.
Katsikeas (1994) and Dean et al. (2000) pointed out that as the role of exporting in a nation’s economy becomes increasingly important, interest in the export behaviour of firms has grown. The increased attention in the literature is explained by the fact that there is a growth of countries with balance of payments deficits. It is acknowledged that an increase in the exports of a country has a positive effect on the growth of a countries economy. Furthermore, exporting is an
attractive expansion mode due to the commitment requirements to the company’s resources when compared to other types of international activity, such as joint ventures and foreign
1.1 Problem Indication and Main Research Question
Export performance is a very widely studied subject. Already in the sixties researchers have studied the export behavior of firms. In the seventies, Bilkey (1978) was the first who integrated the literature available in that time on export behaviour. His study showed that there are basically two groups of factors that influence a firms’ export behaviour; External (chambers of commerce, industrial associations, banks, government agencies, and other firms) and internal factors
(management and firm characteristics). However, it showed that of the forty-three studies that were used in this article, only four focussed on export performance. Since Bilkey’s study (1978) is focussed on the developmental process of the export firm, the outcomes are less relevant for our study. However, his first categorization of the factors influencing export forms a basis for research on this subject. In the following decades a number of similar studies inspired by Bilkey (1978) were conducted. They all try to assemble most research on export behaviour to that date and showing fields for further research. Furthermore, in this period more attention has been given to export performance. The next decade of research was integrated by Aaby and Slater (1989). Zou and Stan (1998) integrated the literature between 1987 and 1997. The research has shown that the main factors influencing the export performance are the internal and external factors. Considering the internal factors Zou and Stan (1998) distinguish four groups; a firms’ export marketing strategy, management attitudes and perceptions, management characteristics and a firms’ characteristics and competencies. Similarly, they distinguish three groups of external influences; Industry characteristics, foreign market characteristics and domestic market characteristics. The factors that are used from the groups will be discussed in chapter 2.2. Additionally, the goal of the papers above was to trace the new developments in the last decade, categorize and identify trends in export performance.
Finally it can be stated that based on the previous research it became clear that all studies on export performance were performed on a company level and almost never on a county level. When the studies are performed the focus is usually on one country. The study of Prefontaine and Bourgault (2002) is one of the few in which a comparison is made between two countries. Due to the limited studies in which a comparison is made between two countries we choose to conduct a study is such a way.
In order to narrow the focus of this study down we choose SMEs from the United Kingdom (UK) and France in the automotive industry. The reasons for this choice will be explained in chapter 3.1. The main research question is as follows:
“How do internal and external factors differ in their influence on the export performance between French and UK SMEs active in the automotive industry?”
In order to answer this research question the first step is to build a theoretical framework to find possible determinants, and possible relationships between these determinants and export
performance using literature. Since the timeframe is limited, this study will not test all the variables studied in the research mentioned in this chapter.
1.2 Significance of the Research
Insight into the factors that influence the export performance of MNE’s can be useful for the decision making process of managers when improvement or understanding of the export
1.3 Research Outline
2. THEORETICAL BACKGROUND 2.1 Automotive Industry
Rodriguez and Rodriguez (2005) and Barrios et al. (2003) showed that a firms’ capacity to export and sell products in foreign markets depends upon its competitiveness, which resides from intangible resources. This literature has shown the importance of technology on achieving this competitiveness as an important factor influencing the export performance. Other research (La Vinh et al. 2005) showed that there are therefore differences between the factors influencing export performance in the service and manufacturing industry. For example, they argue that technical facilitation is a more important factor influencing export performance for industries characterized by a low degree of face-to-face contact than those characterized by a high degree of contact. This makes it clear that different factors influence export performance among industries. Therefore, we need to find specific factors influencing export behaviour in the automotive industry. In this chapter we will elaborate on the current situation of the automotive industry, focussing on these influences on export performance. We will start with some descriptive statistics, after which the differences between the UK and France position in the automotive industry will be explained.
-Table 2.1.1.1: Number of Companies from the UK Automotive Industry-
Source: http://www.autoindustry.co.uk/statistics/
Table 2.1.1.2 shows this ongoing decline in jobs. In the last decade one of five employees has lost his job. Finally, considering the trade balance of the automotive industry, table 2.1.1.3 shows a structural trade deficit. Over the past ten years the trade deficit has more than doubled.
-Table 2.1.1.2: Number of Employees in the UK Automotive industry-
Source: http://www.autoindustry.co.uk/statistics/
-Table 2.1.1.3: Trade Balance of the UK Automotive Industry-
Source: http://www.autoindustry.co.uk/statistics/
The main factors in causing this deterioration of the UK sector are the exchange rate of the British Pound and the emerging competitors. We start here with the role of the British pound on the UK automotive industry. According to Handelman (2003) the rising pound has had a
the high exchange rate of the pound, manufacturers and exporters had trouble with maintaining their turnover and consumers are paying more for their cars than any other country in Europe (Lewis, 2003). This situation has brought increased attention to the UK discussion on joining the Euro zone. “Without being in the euro, the disadvantage is too big a wall for the UK industry to climb. It’s causing a lot of problems” (Glover, 2002).
A more recent report by the House of Commons (2005) shows that this problem is still significant in the automotive industry in the UK. “There can be little doubt that non-membership of the Euro has created difficulties for the UK automotive sector … The vehicle manufacturers would mostly prefer the value of the euro to be higher still, the issue of predictability is of greater concern at the moment. Exchange rate fluctuations can significantly reduce margins, which are already tight.” However, the automotive sector is one of many aspects that have to be considered when deciding whether the national economic interest is best served by UK membership of the EMU.
A second strong factor in this situation is the increased competition from emerging countries in the automotive industry. Cars from China and parts from India are seriously threatening the UK position. This trend did surely not develop over night. China and India are at the moment already well established producers of auto parts and their network in extensively linked with the western car producers (MacNeil and Chanaron, 2005). Especially the Chinese industry is reaching a new phase that will shift from manufacturing only for the fast-growing local market to become an export base for the rest of the world too. “China is closing the quality gap and building a base of low-cost suppliers that could eventually allow it to unleash inexpensive, well-made cars on the West. And because local production capacity of 3 million vehicles a year is currently outstripping demand by about half a million vehicles, there are already a lot of wheels looking for a garage” (Bremner et al., 2005). In approximately five or six years the Chinese are ready to start selling competitively priced cars overseas keeping in mind that a Chinese auto assembly worker earns two dollar an hour versus 22 dollar in Korea and nearly 60 in the US. (Bremner et al., 2005). Additionally, an international comparison of average hourly labour costs from 20012 showed that
labour costs in the UK ($24,2) are much higher than those of France ($15,8), Korea ($7,3) or Germany ($18,6).
Furthermore, the global ambition of India is already starting to pay off. India’s auto makers and suppliers are working toward the country becoming the region’s small-cars export hub, while making a concentrated push into Europe and other foreign markets (Sudhakar, 2005).
Especially, the Indian auto component industry has grown at a cumulative growth rate of 21% annually in the past five years and will be able to continue this growth until approximately 2015 (Katz, 2006).
Finally, when table 2.1.1.4 is considered it can be stated that the situation in the near future is not about to change. In the coming seven years the UK car production capacity will decrease with 20%. This prognosis was made by the PricewaterhouseCoopers automotive institute which has proven it’s accuracy in the past.
-Table 2.1.1.4: Vehicle Production Capacity Data of the UK and French Automotive Industry-
Source: http://www.autofacts.com/datapage.asp?LEVEL1KEY=3&LEVEL3KEY=0&internallink=1&sessionKey
AT Kearney (2001) stated that the UK car assembly will inevitably decline. “Those companies that do remain do so for historical rather than economic reasons and can only be maintained by sourcing an “unnatural” percentage of components from the euro zone. This trend, together with the increasing move of assembly to mainland Europe, will also drive tier 1 sourcing in the same direction: As components sourcing moves to Europe as a “quick fix” to the exchange rate problem, UK supplier’s volume will sink below critical mass.”
20% of production capacity. So, how is it that France is better managing the changes in the world landscape of the automotive industry?
Firstly, table 2.1.1.5 shows that the productivity in GDP per employee in France is 10% higher compared to the UK, with a lower average cost of labour than the UK. France has a large pool of trained and experienced employees available (Invest in France agency, 2002) as opposed to the UK, where there is a shortage of technical and engineering skills at all levels. 74% of firms in the sector have a shortage in these areas of expertise3.
-Table 2.1.1.5: Productivity in GDP per Employee per Hour in USD in the UK and French Automotive Industry-
Source: invest in France agency
Nevertheless, France will loose some employment to international competition to lower labour cost countries such as Morocco, Tunisia and Spain (Automotive News Europe, 2006).
Consequently, in the period 2004-2005 France has lost one percent of employment4. One of the leading concerns is EU expansion. "As the EU stretches into the Czech Republic, Slovakia, Lithuania and other East European nations next year, there is apprehension that they could usurp manufacturing jobs from France, as well as other Western European nations” (Kelly, 2003). This however, is not a short term concern.
Secondly, another interesting fact is that French subsidiaries of foreign groups represent to thirds of the sectors turnover and three quarters of the export. Figure 2.1.1.6 shows the dominant influence of foreign companies in the French automotive industry.
3http://www.ukinvest.gov.uk/2/d/10191/en/GB/1.0.html
4http://www.acea.be/ASB20/axidownloads20s.nsf/CategorizedOverviewACEA?OpenForm&Language=English&cat
-Figure 2.1.1.6: French subsidiaries of foreign automotive companies-
Source: http://www.investinfrance.org/France/Newsroom/Publications/publication_2002-09-03_en.pdf
Finally, the amount of FDI differs severely between France and the UK. Table 2.1.1.7 shows that the number of FDI projects in France outweighs the number of projects in the UK. Together with the other factors negatively influencing the UK it is quite assumable that a grim reality awaits the UK automotive industry. New investments are needed to keep innovating. This is an important factor in the race of staying competitive (Wilson, 2003).
-Table 2.1.1.7: FDI in the Automotive Industry- Country of Destination 2004 Percent of Total 2004
2.2 Hypotheses
Partly based on the literature found and partly based on data availability we have used seven variables with a relation towards export performance. These variables are number of employees and total turnover, which together represent firm size, type of ownership (domestically or globally ultimately owned), uncertainty avoidance index, power distance index, index of
economical freedom and GDP. This chapter will review the literature inherent to the hypotheses. The hypotheses are divided between those related to internal and external influences. Using the model of Zou and Stan (1998) which was partly based on the model of Aaby and Slater (1989) chapter 1.1 mentioned that the internal factors are divided into four groups and the external into three. The internal factors that will be used in this study are firm size and ownership type and belong to the group of firm characteristics. The external factors that will be used are culture, economical freedom and country size who belong to the domestic market characteristics. Therefore, we use one group from both internal and external factors. The reason for selecting variables from these groups is partly based on data availability which will be further elaborated on in chapter 3.1. Due to the selection process we were forced to use less countries and variables that were initially part of the conceptual model. Furthermore, the reason for selecting the
variables that are used in this study to explain export performance in the automotive industry is based on developments in it. Since there are no studies performed that relate export performance to the automotive industry we have to deduct the variables to some or greater extend from these developments which are described in Chapter 2.1. The decrease in the number of companies and employees are related to firm size which reduces the economies of scale and therefore
performance. Culture was selected as a variable because of the differences in productivity between France and the UK which lead to the assumption that different cultures create different performance. The increasing deficit on the trade balance lead to the assumption that country size influences performance. Finally, ownership type was selected due to the dominance of foreign companies in the French automotive industry. Economical freedom was selected because of the increasing competition in the automotive industry which most likely will influence these variables in their effect on export performance.
2.2.1 Firm size. In the literature firm size is probably mentioned the most often as a firm characteristic influencing export performance. Edwards et al. (2005) collected a number of arguments why this assumption seems to be valid. Firstly, internationalization requires a variety of resources. Resource scarcity limits the ability of small firms to reach advanced stages of internationalization. Secondly, smaller firms may be risk averse because of insufficient
information and the impact of international errors. Thirdly, it is more likely that firms undertake growth in their domestic market first. When the opportunities for growth have been limited the firm will commence exporting. By this stage the firm will have grown. Finally, economies of scale make a firm more competitive and therefore help in the capacity to pursue export opportunities.
This would lead naturally to the assumption that there is a positive relation between firm size and export performance. However, the empirical findings have been mixed. Some studies report a positive influence where others report a negative or even no significant influence. After 30 years of research there is still not a satisfactory explanation for this relation (Verwaal and Donkers, 2001). To illustrate this point; Chetty and Hamilton (1993) have summarized the published literature from all parts of the world relating to firm size. From the 29 studied integrated in the summary, 6 showed an insignificant relation, 17 a positive and 6 a negative relation. Since the research showed a majority of positive relationships, we will assume this as well. This leads to the first hypothesis:
H1: There is a positive relation between firm size and export performance in the automotive industry.
ownership and firm performance. However, there has not been yet extensive studies on the effect of ownership type on export performance. Those that have been performed have been conducted on a single country (Katrak, 1983, Bottasso and Sembenelli, 2004 and Rasiah and Gachino, 2005). These studies also show that foreign ownership has positive relationship with export performance as opposed to domestically owned firms. This brings us to the next hypothesis:
H2: Domestically owned SMEs have a lower export performance as opposed to foreign owned SMEs in the automotive industry.
2.2.3 Country culture. A country’s culture has long been identified as a key characteristic underlying systematic differences in business behaviour (Hofstede, 1994). Country culture will be defined here as “the collective programming of the mind that distinguishes the members of one group or category of people from another” (Hofstede, 2001).
Nevertheless, “Despite the large body of literature on the link between culture and company behaviour, the influence of country-of-origin on export market research and export performance has been largely ignored” (Voerman et al., 2002). Hofstede (1994) and Erramilli (1996) showed that it is possible to connect export performance to the uncertainty avoidance and power distance that exists within firms.
“Uncertainty avoidance (UA) is the extend to which the members of a culture feel threatened by uncertain of unfamiliar situations. This feeling is partly being expressed by a need for
predictability” (Hofstede, 2002). Therefore firms from countries with a high UA are likely to be highly reluctant to engage in export activities as opposed to firms from countries with low UA. However, it should be noticed that there are some outliers that contradict the relationship between the degree of uncertainty avoidance and export performance. Based on GDP and export data from the OECD5 and the UAI of Hofstede (2002) table 2.2.3.1 was made to indicate the percentage of export in GDP related to the UAI. If the theory should hold the percentage of export in GDP should increase as the UAI decreases. Overall, table 2.2.3.1 shows this relationship.
-Table 2.2.3.1: Relative export and the UAI, 2005-
Country UAI GDP (in Billions) Export (in Billions) Export/GDP in %
Greece 112 143,9 1,43 0,994 Portugal 104 116,3 3,18 2,73 Japan 92 4494,1 49,7 0,995 Belgium 94 249,4 27,86 11,171 France 86 1430,1 38,32 2,68 Spain 86 680,8 15,59 2,3 Mexico 82 636,2 17,58 2,76 Italy 75 1132,8 30,63 2,7 Austria 70 208,3 8,83 4,24 Germany 65 1961,8 80,81 4,12 Finland 59 137,8 5,5 3,99 UK 35 1619,5 32,14 1,985 Netherlands 53 408 33,83 8,29 Sweden 29 270,3 10,84 4,01 Denmark 23 171,5 6,9 4,023
There are only 2 outliers in the selection of countries; Belgium and the UK. There is no particular reason why these countries should be different from the other countries because of special
circumstances. So, how can these outliers be explained? Partly, based on Hofstede (2002), it can be explained by the fact that uncertainty avoidance if often confused with risk avoidance. Risk is often expressed in a percentage of probability that certain events will occur. Uncertainty, just like fear, is based on a feeling; not based on something that can be expressed in a percentage.
Uncertainty occurs in situations in which everything can happen but we have no idea what. When uncertainty is formulated as a risk, it stops being a source of fear. It can become accepted as routine, like riding a car. Perhaps it is possible that in this situation Belgium is better able to accept fear as a routine as opposed to the UK. However since there is no study on these deviating relations, we ignore the few outliers and formulate the hypothesis as follows:
H3a: There is a negative relation between a firms’ degree of uncertainty avoidance and its export performance in the automotive industry.
foreign countries to obtain more control. For this reason we expect that firms with a high PD will have a higher export performance as opposed to firms with a low PD. However, again there are deviations from the theory according to table 2.2.3.2. Similarly, this table was built like 2.2.3.1 and indicates the rankings of the power distance and the export in a percentage of the GDP. In this case however the matter concerns not a few outliers but an almost reverse effect. It seems like lower PDI scores have greater export percentages.
-Table 2.2.3.2: Relative export and PDI, 2005-
Country PDI GDP (in Billions) Export (in Billions) Export/GDP in %
Mexico 81 636,2 17,58 2,76 France 68 1430,1 38,32 2,68 Belgium 65 249,4 27,86 11,171 Portugal 63 116,3 3,18 2,73 Greece 60 143,9 1,43 0,994 Spain 57 680,8 15,59 2,3 Japan 54 4494,1 49,7 0,995 Italy 50 1132,8 30,63 2,7 Netherlands 38 408 33,83 8,29 Austria 36 208,3 8,83 4,24 Germany 35 1961,8 80,81 4,12 UK 35 1619,5 32,14 1,985 Finland 33 137,8 5,5 3,99 Sweden 31 270,3 10,84 4,01 Denmark 18 171,5 6,9 4,023
Nevertheless, since no study to this date is performed on the negative relationship between export performance and the PDI, let alone, the relationships with different industries, we are forced to use the existing theory and eventually, when necessary, explain this contradiction, when the tests are performed and prove otherwise. Therefore, the next hypothesis is:
2.2.4 Country’s government. Most research of governmental influence on export performance has focussed on their restrictive role. On the other hand, governments also provide support for exporters. Frequently, this is in the form of information or assistance provided to exporting companies in special programs or institutions. Holzmüller and Kasper (1991) and Holzmüller and Stöttinger (1996) found an positive effect of the perceived quality of export consultancy provided by the Federal Chamber of Trade, by financial institutions, and by government agencies on the export ratio. Therefore it can be stated that governments influence export performance by stimulating or discouraging (through export tariffs and quota’s) it. Tyson (2003) illustrates this by using the quotas on Chinese textile products as an example. The Chinese producers where affected by these quota’s since they are not allowed to export a certain amount of export products. Rake (1981) mentioned already twenty five years ago that African countries are battling against trade restrictions and barriers imposed by developed economies, an ongoing process to this date. This shows how important it is for a country to export. Finally, taking trade theory into account, the elimination or decrease of tariffs and quotas will accomplish that all countries increase in national income and therefore in welfare. Furthermore, it should be added that protection of a industry that is vulnerable might be a valid argument to improve performance, but this will only be effective in the short run after which this protection causes the performance to drop (Dunn and Mutti 2004). This brings us to the fifth hypothesis:
H4: There is a positive relation between the economical freedom created by a countries government and a firms export performance.
2.2.5 Country size. “In Europe, economies such as The Netherlands, Belgium, Denmark and Austria, are traditionally dependent on international exchange. To maintain the standard of living, these countries face the increasing challenge of establishing cross-border relationships” (Baldauf et al., 2003). This leads to the assumption that smaller countries, with smaller domestic markets are more quickly forced to export as opposed to firms from big countries. This
assumption is confirmed by Egger and Pfaffenmyar (2005) who found that exports and affiliate sales increase as a country is smaller in size. Therefore, the fifth and final hypothesis is as follows:
3. METHODOLOGY
Most research is determined by the availability of data. Due to the limited time frame it is not realistic to obtain primary data through a survey, which is common in studies on export
performance. Secondary data will be retrieved from AMADEUS6. That’s why we need to filter the information until we are able to build a workable data set. The criteria that were used revolve around the following assumptions. There should be enough information to get significant results and countries and industries need to be selected that can be integrated in the dataset. Furthermore, this justifies the need for a description of the selection process after which the operationalization, study type, sample size and conceptual framework will be discussed.
3.1 Selection Process
The first step was to select countries of which data on export turnover could be retrieved, since this is the most important variable. The year of focus is 2004 since this is the year that showed available data in all the company’s reports. In our search we were limited to the list of countries from AMADEUS; the database of which we will retrieve the firm characteristics. This led to a selection of France, Greece, the UK, Slovenia, Hungary and Croatia. The second step was to check whether environmental data could be found for these countries. This step eliminated Slovenia, Hungary and Croatia. The data of these countries was too segmented to be used in the dataset.
The type of firms targeted in the selection process were SMEs. SMEs are companies that employ less than 250 people and have a turn over of less than €50 million. The reason for this choice is the possibility to generalize the outcomes of this study. “Knowledge of export behaviour of SMEs is crucial since these enterprises represent a very large proportion of all the firms (77-99%) in most economies. They also account for a large share of the worlds export activity and have been directly linked to job creation and economic growth” (Prefontaine and Bourgault, 2002). These firms provide for almost two third of the total overall employment in the EU7.
6 AMADEUS contains financial data of 250.000 European companies 7
The third step eliminated integrated subsidiaries from foreign countries. These integrated
subsidiaries operate independently from their local environment and as an extension of the parent company, with cash-flows and general business lines highly interrelated with those of the parent (Eiteman et al., 2001). Exports from these subsidiaries should be excluded from the data set since their export performance is influenced unrelated to the firm characteristics and environmental influences mentioned in chapter 2.2 as opposed to independent firms. A division was made between domestically and independent globally owned firms.
The final step was to select industries. Chapter 2.1 already explained that such a division is necessary since different industries react differently in their influences on export performance. From the AMADEUS database industries were selected that offered the most firms. These industries are: Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuel (from this point mentioned as the automotive industry), Manufacturing and Real estate activities. This final step eliminated Greece since the filtering did not provide enough firms to achieve significant results. Furthermore it eliminated the industries manufacturing, since manufacturing is a too general categorization, and real estate, because it offered to little companies to use in the dataset.
To sum up, this study will deal with the differences in internal and external influences on export performance between SMEs from the automotive industry, from France and the UK.
Due to this selection process we were forced to drop one of our initial internal factors influencing export performance; R&D expenditures. Furthermore this also explains the reason why we use only two groups from the seven (four internal and three external) that were given by Zou and Stan (1998) mentioned in chapter 2.2. AMADEUS has a limited amount of variables relevant to this study. Constructing a database covering variables from all seven groups goes greatly beyond the time availability for this study.
3.2 Operationalization
The operationalization explains how the firm characteristics and environmental influences will be measured.
3.2.1 Firm size. The reason why there is such a discrepancy in the results on the relation between firm size and the export performance lays in the fact that firm size is operationalized differently in many studies. Calof (1994) explained in his research that; “Differences in the measurement of size and different sample frame characteristics (geographic focus, industries and firm size) were evident in many of the studies reviewed for this paper, and may help explain some of the inconsistencies in study findings. Up to this day, there still has not been a consistent operationalization for firm size. Firm size is measured either by number of employees or sales. Beside that, most studies sampled the firms from a single country of industry. To overcome the problem of being unable to generalize, this study will measure firm size in number of employees and total sales. Because, “there is increasing evidence that export performance is considered as a multifaceted construct and should not be captured by a single indicator” (Cavusgil and Zou, 1994). This data will be retrieved from AMADEUS.
3.2.2 Ownership. In AMADEUS it is possible to select companies with an ultimate global or domestic owner. This led therefore to two categories. A global ultimate owner is
operationalized as a shareholder from a global firm owning 50.01% or more shares from the SME. A domestically ultimate owner is a France or UK shareholder owning 50.01% or more shares from the SME.
3.2.3 Country culture. Country culture will be defined in the uncertainty avoidance index (UAI) and the power distance index (PDI) of Hofstede (1994). The data will be retrieved from Hofstede’s book (2002) and his internet site8. Considering the UAI, a higher ranking indicates countries which are more uncertainty averse as opposed to countries with lower scores. The PDI shows the ranking of countries towards their acceptance of power. High rankings show countries
in which less powerful members of an organization expect and accept that the power is unevenly divided as opposed to lower ranking countries.
3.2.4 Country’s government. To measure the economical freedom of domestic companies that is caused by the policy of the French and UK government, the ordinal scales of the index of economical freedom will be used. This data can be retrieved from the internet site of The
Heritage Foundation/Wall Street Journal Index of Economic Freedom9. The index of economical freedom measures 161 countries against a list of 50 independent variables divided into ten broad factors of economical freedom. These factors apply to trade, fiscal burden, government
intervention, monetary policy, foreign investment, banking, wages and prices, property rights, regulation and the informal market. Low scores are more desirable. A higher score on a factor means a greater level of government interference in the economy and less economic freedom enjoyed by a country.
3.2.5 Country size. Country size will be defined as the Gross Domestic Product (GDP) of that country. This data will be retrieved from the database of the OECD10.
3.2.6 Export performance. This data will be retrieved from AMADEUS and will be measured by the percentage of the export turnover in total turnover. This export-to-sales ratio was also used in the study of Majocchi et al. (2005). This ratio is useful because it is by far the most widely used in empirical research.
3.3 Type of Study
This study can be characterized as a comparative type of study. According to the theory of Thomas (2002) this is a study conducted in two countries (France and the UK) and used to point out similarities and differences. Furthermore, this study is not longitudinal, since it involves the observation of firm characteristics and environmental influences in 2004.
3.4 Tests
To compare the two populations and test whether there are significant differences between the UK and France the following tests will be performed;
• Hypothesis 1; A multiple regression analysis will be performed since the variables, total turnover, number of employees and export performance, are all interval data and because the number of employees and total turnover need to be paired.
• Hypothesis 2; An independent sample t-test will be performed since the variable ownership is divided into two categories (domestically and globally ultimately owned) and concerns therefore nominal data.
• Hypotheses 3a, 3b, 4 and 5; These hypotheses all revolve around a variable with only two scores. Therefore this data can be considered as nominal data when the two scores represent two categories. A chi-squared test will be performed to test these hypotheses.
3.5 Sample Size
After the selection process was described in chapter 3.1, table 3.5 shows the number of firms that determine the size of the population.
-Table 3.5: Population automotive industry- Population Automotive Industry Domestically ultimately owned Global ultimately owned Total UK 31 52 83 France 220 116 336
multiplier”, which is an adjustment factor that needs to be taken into consideration under these circumstances (Burns and Bush, 2000). Unfortunately, due to the relative small size of the
industry population the formula did not function. Therefore we choose to use all the companies of the population since there is little known about these situations. By using the total population (419 companies) we can be sure that a sufficient number of companies is selected to secure significant and reliable results.
3.6 Conceptual Model
Considering chapter 2 to 3.5 it is now possible to construct a conceptual model represented in figure 3.6
-Figure 3.6: Conceptual Model-
4. RESULTS
Before we start with the hypotheses some background information is provided for understanding the nature of the data. Table 1 in the appendixes shows the descriptive statistics of the number of employees, turnover and the export turnover in a percentage of the total turnover (ET/TT). The number of employees varies between 2 and 253, the turnover lies between 2007 and 53.837 euros (in thousands) and the percentage of export turnover in total turnover lies between 0.010 and 100. Furthermore, the uncertainty avoidance index (UAI) of the UK is 35 and the UAI of France is 86 (Hofstede, 2002). This means that firms in France avoid uncertainty more than firms from the UK. The Power distance index (PDI) of the UK is also 35 and the PDI of France is 68 (Hofstede, 2002). This means that the power distance/hierarchy in French firms is greater as opposed to firms from the UK. The index of economical freedom (IEF) of 2004 for the UK is 1,84 and the IEF for France is 2,6811. This implies that firms in France have less economical freedom than firms from the UK. Finally, the GDP for the UK is 2.124.462.631 and for France 2.046.735.010 (in dollars).
The next step is to test the hypotheses. Before the tests are discussed it is important to note that the α in all the tests is set on 0.05. When we start with testing the relation between firm size and export performance, chapter 3.4 made clear that a multiple regression analyses would be
performed. However, the variables of firm size are tested separately first because it is important to find out in the thoroughness of the analyses whether there is correlation between the variables. The correlation tests that are performed are Pearson correlation tests. Starting with the UK, table 2 shows the correlation between the number of employees and the ET/TT. The correlation of -0,065 indicates that there is no correlation between the two variables. Table 3 shows that this is the same for the correlation between the total turnover and the ET/TT. With a correlation of 0,089 it is clear that there in no relation between the two variables.
Continuing with France, table 4 shows a significant relation between the number of employees and ET/TT. The correlation itself (0.290) however is rather weak. Table 5 additionally shows no correlation between the total turnover and the ET/TT.
Finally, when that data of both countries is taken together the same tests can be performed. Table 6 makes clear that there is a significant relation between the number of employees and the ET/TT. The correlation of 0,270 however is weak. Table 7 also shows a significant relation between the total turnover and ET/TT. Again the correlation (-0,131) is weak.
In order to answer the first hypothesis completely it is now necessary to perform a multiple regression analyses in which both variables are taken into account. Table 8 represents the result of the multiple regression of the UK, between the number of employees, total turnover and the ET/TT. It becomes clear that there is no regression between the variables. The test shows no significance and the t-values are to low (0,915 and 1,063). In order for the multiple regression to be significant the t-values must be higher than 1,96 or lower than -1,96. This means that there is no relation between the firm size and export performance. To conclude this section on the first hypotheses, table 9 represents the French multiple regression test between the number of employees, total turnover and the ET/TT. The outcome of the multiple regression shows a
significant relation (0,000 and 0,018) between the variables. Furthermore the T-values (6,048 and -2,368) confirm this by exceeding the t-value requirements for being significant. Therefore, it can be assumed that there is a positive relation between firm size and export performance for the French companies. This however, cannot be assumed for the UK companies since the multiple regression showed no significant relation.
The second hypotheses stated that domestically owned firms have worse export performance than foreign owned firms. In order to test this hypothesis an independent sample t-test was performed. However, separate chi-squared tests will be performed firstly to be able to state how the variables interact. Beginning with the UK, table 10 represents the domestically ultimately owned
domestically ultimately owned companies and table 13 the globally ultimately owned. Both chi-squared tests are not significant with 0,273 and 0,249.
The next step is to combine the two ownership types on a country level and perform the independent sample t-test. Table 14 indicates that there is no difference in export performance between the to ownership types. The test shows t-values of 0,562 and 0,565 and a significance level of 0,576 and 0,574. It can therefore be assumed that the second hypothesis is not confirmed for the UK.
Table 15 represents the outcome of the t-test for the French companies. With a significance level of 0,000 and t-values of -5,009 and -4,300 it can be assumed that there is a significant relation. Therefore, it can be assumed that French domestically ultimately owned firms do have a lower export performance than French globally ultimately owned firms. Consequently, the second hypothesis is assumed to be significant for France and not for the UK.
The remaining hypotheses were tested using the chi-squared test. Since there are only two categories it is not possible to test the countries separately since one category can not be used in performing the chi-squared test. Since these last four variables (the UAI, PDI, IEF and GDP) have two categories the outcome of the tests are the same. Therefore, the outcomes of the tests are put together in table 16-18.
The only separation that could be made was for the distinction between ownership types. Table 16 and 17 show that only the domestically owned firms have a significant relation (0,016) with the UAI, PDI, IEF and GDP, as opposed to the globally owned firms who have no relation with these variables.
Finally, while answering the hypotheses it can be assumed that, based on table 18, they are all significant (0,004). Therefore, it can be assumed that:
• There is a negative relation between uncertainty avoidance and export performance. • There is a positive relation between power distance and export performance.
• There is a positive relation between the degree of freedom created by the government and export performance.
5. DISCUSSION
In the dynamic and recent quick changes of the automotive industry landscape, only few
researchers seek for ways to improve the export performance of these firms. The objective of this thesis is to examine the factors influencing this performance. Satisfactory, the results showed some significant relations which will be discussed in this chapter. An attempt is made to provide an explanation for the differences between the UK and France.
The results showed that considering firm size, there is a relation with export performance of French SMEs but not with SMEs from the UK. Chapter 2.2.1 already stated that many researchers have found different relations. This next section will explain the different relation towards export performance between France and the UK. Katsikeas et al. (1995) have found that in a European context differences can occur relevant to firm size and export performance. For example, Gourlay and Seaton (2003) found a positive relation. Nevertheless, they also state that the significance relation between firm size and export performance depends upon industry. This is linked to the theory that different industries have different fixed costs and therefore differ in their export performance (High fixed cost industries will have a slower process to export as opposed to low fixed cost industries). Since there has been no research on the export performance of the automotive industry we can only rely on our results and explain the none relationship of the UK SMEs with the use of other, not automotive related, literature.
Diamantopoulos and Johnston (1988), Cooper and Kleinschmidt (1985), Czinkota and Johnston (1983), all found that there is no relation between firm size and export performance and that SMEs are quite similar in their behavior. “This indicates that a firm does not need to forego export opportunities or discard exporting as a growth strategy simply because it is small”
The reason that there is a relation between firm size and export performance in the French SMEs, could therefore be related to their sufficient size what enables them to make more use of
organizational recourses, economies of scale and lower levels of risk about foreign markets and operations (Katsikeas et al., 1995). This is confirmed by the ratings on the European Innovation Scoreboard which made clear that France, beside Germany, is the most innovative country in the automotive industry (Hollanders and Arundel, 2005).
The results showed that the second hypothesis was only partly confirmed. It could be assumed that only in France, globally ultimately owned firms from the automotive industry, outperform domestically owned firms in relation to export performance. A possible explanation for this difference is that the French globally owned firms have certain advantages over UK globally owned firms. French SMEs have, as noticed in chapter 2.1 a larger source of technical expertise (employees). Furthermore, the average larger French SMEs (see table 19 and 20) benefits more from economies of scale and information inflow. Finally, these firms have a higher monopoly and bargaining power and better access too finance (Kumar, 2001).
Nevertheless, other research has shown a significant relation between globally owned UK companies and export performance. Truett (2005) found that three British car companies thrive better under global ownership. Accordingly, these factories “have new, state-of-the-art
production equipment, paid by the foreign companies that own them. Also, workers in these plants have been retrained to build cars the modern way, using the best equipment available”. This is confirmed by other research. Dosoglu-Guner (2000), also found that externally owned firms show more willingness to export activities.
Continuing, how is it then possible that this is not the case for UK globally owned firms? A study of Griffith (1999) could partly provide an answer. She found that the performance of globally owned firms is not higher than domestic owned firms because these firms operate on a higher technological frontier. The differences in levels of total factor productivity are relatively small. The reason for this could lie in the insufficient investments made in the UK automotive industry (Dosoglu-Guner, 2000).
study. The conclusion here is simple; some cultures have more anxiety than other. Therefore, the degree of uncertainty avoidance differs between countries. For the UK this leads to a weak loyalty to employer and short average duration of the employment. Furthermore, innovations are welcomed but not necessarily taken seriously (Hofstede, 2001). For France an opposite reality is visible; there is a strong loyalty to the employer, long average duration of employment and technical innovative solutions (Hofstede, 2001). It is these uncertainty avoidance effects in working situation that determine the difference in the current situation of the UK and French automotive industry. As chapter 2.1 showed, the reason why the UK industry is doing so badly, among others, is a lack of certified employees. Furthermore, it was also noticed that investments were needed to keep up constant innovation. Not surprisingly, the level of investments in France is much larger than in the UK.
Strangely enough, this contradicts the outcome of the hypothesis. The doubts created by the outliers are therefore in this case proven. According to the test it could be assumed that of the two countries, a lower UAI country, the UK, has a better export performance as opposed to a higher UAI country, France. A possible explanation for the fact that the high UAI of France does not seem to interfere with its export performance is that the uncertainty is overcome by the use of export intermediates, especially in unfamiliar markets. These intermediates can help maximize economies of scale and reduce transaction costs (Isaak, 2002), and help to accept fear as a routine, thereby lowering it.
Hypothesis 3b was also found significant. Therefore, french firms which have a higher power distance as opposed to UK firms, have a better export performance. This difference in
performance can be explained by the fact that; “cultures with high power distance apparently generate decision makers with a great penchant for centralized authority and autocratic management” (Hofstede, 2002). Firms dominated by these decision makers tend to maintain control over their foreign operations by establishing fully- or majority-owned subsidiaries. Firms originating from nations with low power distance cultures, on the other hand, show greater willingness to decentralize their operations by sharing control with foreign partners” (Eramilli, 1996). When this is considered this could mean that the export activity of both countries is equal but the export performance is different because the French firms stay in control of their
Therefore, earlier doubts on the validity of the theory are not confirmed for the automotive industry.
As expected from chapter 2.2.4, a high degree of economical freedom created by a government causes a higher export performance. The results showed that the lower score of the UK on the IEF confirmed this earlier statement. Taylor (1995) illustrates this by giving an example from the automotive industry. Peugeot seems to be weak everywhere outside France, where it is protected by stiff import barriers from foreign competitors. Due to this, export performance is affected. Furthermore, basic trade theories explain that the removal of trade barriers will lead to the increase of overall welfare (Dunn and Mutti, 2004).
6. CONCLUSIONS AND LIMITATIONS
Our research has contributed to the expansion of the existing literature on the automotive industry. Theoretical and empirical evidence proves that there exist differences between the internal and external factors influencing export performance of French and UK SMEs. The tests have shown that firm size and ownership type have a significant influence on export performance with the French SMEs, but not with the UK SMEs. Furthermore country culture, country
government and country size have shown differences between France and the UK. A low UAI and IEF indicated that the UK had a better export performance than France. The high PDI and lower GDP caused France to have a better performance than the UK.
The discussion made some interesting relations to explain these differences. The factors that seemed to be responsible for the differences between the two countries are R&D expenditures, investments in HRM and most important; innovation. Innovation is the driving force in the process of staying competitive in the automotive industry. Through R&D expenditures and investments in HRM it is possible to keep innovating and therefore assure a competitive export performance. As mentioned before, it is the lack of, a slow process of, innovation in the
automotive industry that is causing the UK to have a lower export performance as opposed to France. In the earlier stages of constructing this thesis innovation was selected as an important variable influencing export performance. Unfortunately, all research is determined by the
availability of data. Therefore, innovation could not be used as a variable. Furthermore, due to the use of the database AMADEUS, only France and the UK could be selected.
Future Research
resources. This literature has shown the importance of R&D expenditure on achieving this competitiveness as an important factor influencing the export performance.
A second point for further research is the testing of the exchange rate on export performance. In this thesis it became clear that this is also an important variable that affects export performance. Therefore, a longitudinal study should be performed to test this relationship.
Thirdly, the doubt created by the outliers in the uncertainty avoidance ranking and furthermore the theory behind it, has been proven just in the automotive industry but raised questions on the validity of the theory. Additionally, the relationship between the variables becomes even more unclear because of the declining performance in the UK automotive industry. Should the UK show a stable or increasing performance in this industry no doubts would exist concerning the validity of the theory. Therefore, in future studies a wider range of countries should be selected covering more countries with different performance. Germany should be selected due to its leading role in the automotive industry, together with some emerging countries such as Czech, China and India.
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APPENDIXES TABLE 1
-Descriptive Statistics of Employees, Total Turnover and Export Turnover in Total Turnover-
N Minimum Maximum Mean Std.
Deviation
Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error
employees 419 2 253 75,82 55,871 1,287 ,119 ,945 ,238 total turnover in th. 419 2007 53837 24211,89 8868,182 ,732 ,119 ,175 ,238 export/total turnover in % 419 ,010 100,000 15,54172 25,455682 1,822 ,119 2,148 ,238 TABLE 2
-Correlation UK; Employees and Export Turnover/Total Turnover-
employees export/total turnover in %
employees Pearson Correlation 1 -,065
Sig. (2-tailed) , ,557
N 83 83
export/total turnover in % Pearson Correlation -,065 1
Sig. (2-tailed) ,557 ,
N 83 83
TABLE 3
-Correlation UK; Total Turnover and Export Turnover/Total Turnover-
export/total turnover in % total turnover in th.
Export/total turnover in % Pearson Correlation 1 ,089
Sig. (2-tailed) , ,425
N 83 83
total turnover in th. Pearson Correlation ,089 1
Sig. (2-tailed) ,425 ,
TABLE 4
-Correlation France; Employees and Export Turnover/Total Turnover-
employees export/total turnover in %
employees Pearson Correlation 1 ,290
Sig. (2-tailed) , ,000
N 336 336
export/total turnover in % Pearson Correlation ,290 1
Sig. (2-tailed) ,000 ,
N 336 336
** Correlation is significant at the 0.01 level (2-tailed).
TABLE 5
-Correlation France; Total Turnover and Export Turnover/Total Turnover-
export/total turnover in % total turnover in th.
export/total turnover in % Pearson Correlation 1 -,017
Sig. (2-tailed) , ,756
N 336 336
total turnover in th. Pearson Correlation -,017 1
Sig. (2-tailed) ,756 ,
N 336 336
TABLE 6
-Correlation UK and France; Employees and Export Turnover/Total Turnover-
employees export/total turnover in %
employees Pearson Correlation 1 ,270
Sig. (2-tailed) , ,000
N 419 419
export/total turnover in % Pearson Correlation ,270 1
Sig. (2-tailed) ,000 ,
N 419 419
TABLE 7
-Correlation UK and France; Total Turnover and Export Turnover/Total Turnover-
export/total turnover in % total turnover in th.
export/total turnover in % Pearson Correlation 1 -,131
Sig. (2-tailed) , ,007
N 419 419
total turnover in th. Pearson Correlation -,131 1
Sig. (2-tailed) ,007 ,
N 419 419
** Correlation is significant at the 0.01 level (2-tailed).
TABLE 8
-UK; Multiple Regression Analysis Firm Size-
Unstandardized
Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) 29,868 10,613 2,814 ,006
employees -5,239E-02 ,057 -,108 -,915 ,363
total turnover in th. 6,083E-04 ,001 ,125 1,063 ,291
TABLE 9
-France; Multiple Regression Analysis Firm size-
Unstandardized
Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) 9,464 3,459 2,736 ,007
employees ,143 ,024 ,335 6,048 ,000
