Title:
THE PERFORMANCE OF JAPANESE SUBSIDIARIES IN MALAYSIA
Authors:
NORHIDAYAH BINTI MOHAMAD
Aichi University and Universiti Teknikal Malaysia Melaka (UTeM)
2-10-31 Tsutsui, Higashi-Ku, Nagoya 461-8641, Japan
norhidayah@utem.edu.my
Fax: +81 52 937 8264
Tel: +81-80 4305 1005
&
YASUO HOSHINO
Professor of Finance and Management, Aichi University and University of Tsukuba
2-10-31 Tsutsui, Higashi-Ku, Nagoya 461-8641, Japan
hoshino@aichi-u.ac.jp
Fax: +81 52 937 8264
Tel: +81 52 937 8264
1
THE PERFORMANCE OF JAPANESE SUBSIDIARIES IN MALAYSIA
Abstract
This paper investigates the relationship between Japanese subsidiary’s performance, entry mode,
dimensional aspects, and international experience. We used a sample of 270 subsidiaries from
Toyo Keizai Inc., Japan Overseas Investments, listed by countries, from 2005 to 2009. The
purpose of this paper is to establish a relationship that is statistically significant, between
Japanese subsidiary performances. A multiple regression model has been applied in this research.
The results reveal that dimensional aspects and international experience had influenced the
subsidiary’s performance. Moreover, a parent companies establishment and performance can
create profit for their subsidiaries to retain their profitability.
Keywords: Entry mode, Foreign Direct Investment (FDI), and subsidiary’s performance
1.
Introduction
This study focuses on Foreign Direct Investment (FDI) and Multinational Companies
(MNCs) with the aim of determining the main factors that contribute to the MNCs subsidiary’s
performance within a developing country. Host countries often associate the inflows of FDI with
a wide variety of benefits; the most common of which, is the transfer of modern technologies.
The extent to which a host country can secure these FDI benefits is likely to depend upon the
2
mode of entry of foreign firms. To maintain or achieve competitiveness and profitability, a
manufacturing firm or enterprise must respond to a range of challenges, including rapid
improvements in technology, declining employment and output, globalization of markets, and
environmental requirements.
MNCs play an important role in the process of global economic integration. Andersson &
Forsgren (2000) reveals in his research that MNCs can provide intangible assets, such as
advanced technology, rather than the MNCs stock of physical capital. The FDI, interconnected
with MNCs, has already become an increasingly vital source for many developing countries to
obtain international capital and advanced technology. Thus, the Malaysian government provides
attractive policies for foreign investors and maintains a free market, in order to retain its existing
investors and attract more potential investors. Therefore, various actions have been taken by the
government to maintain the competitiveness of the country, including the reduction of corporate
tax, down from 27% in 2007 to 26% in 2008; and a further reduction to 25% in 2009. With this,
Malaysia is finds itself amongst the most competitive countries in Asia, for corporate tax.
With all these facilities and incentives provided by the government, Malaysia remained
as a favourable economy to foreign investors, as implied by their FDI position, which grew twofold, since 2001. Continuous reinvestment, as well as new capital injection amongst existing
3
foreign companies, indicates their confidence in the Malaysian investment climate. From 2003
until 2007, manufacturing and financial intermediation were the two main sectors of FDI
recipients (Department of Statistics, 2000).
1.1. FDI in Malaysia
Japan and Malaysia have for a long time, already cultivated a positive and agreeable
partnership, as well as strong bilateral trade and investment linkages. Malaysia’s Look East
Policy and the direct investment of Japanese firms in Malaysia, contributes to the close
relationship between the two countries. The accumulated investment and transfer of technology
by Japanese firms is an encouraging basis for the further development of both countries in the
future.
Malaysia is one of Japans most important economic partners, and vice versa. The
bilateral relationship has been both solid and stable, with close personal ties between both
countries at official and private sector levels. Bilateral trade has significantly lengthened during
the past decades. Referring to Malaysia Economic figures of 2009, Japan was the third largest
export destination of Malaysia (at 71.79 billion Ringgit Malaysia, accounting for 10.8% of total
exports) and the largest source of import (at 14.2 billion Ringgit Malaysia, accounting for 12.5%
of total imports) for the year 2008.
4
In the year 2002, Malaysia was the 10th largest import and export partner of Japan, with
1.4 trillion Japanese Yen (3.3%) and 1.38 trillion Japanese Yen (2.6%), respectively. In 2008,
more than 72% of exports from Malaysia to Japan consisted of industrial goods, while the
remaining percentages were agriculture, forestry, and fishery items. Subsequently, almost all
exports from Japan to Malaysia were industrial goods (Hayashi, 2010).
Furthermore, Table 1 shows the FDI statistics for the three main countries in Malaysia.
Japan indicates the highest composition ratio (31.8) amongst the three countries. In Malaysia, the
FDI for manufacturing (735 firms) and non-manufacturing (686 firms) had a small gap with 49
different companies in the year 2009 (Report and Statistics, 2010).
Insert Table 1 about here
Based on the Japan-Malaysia economic partnership group report in 2003, bilateral and regional
approaches for Free Trade Agreements (FTA) are currently being pursued to further improve the
competitiveness of countries in the region, as seen in the European Union and NAFTA for
Europe and North America, respectively. To achieve similar benefits, the Association of
Southeast Asian Nations (ASEAN) has proposed various partnership agreements between
ASEAN countries and the Asia region, to achieve these similar benefits. Therefore, the ASEAN
Free Trade Area (AFTA), the Framework for Comprehensive Economic Partnership between
5
ASEAN and Japan, ASEAN and China, as well as between ASEAN and South Korea, have been
signed.
In conjunction with these regional approaches, a bilateral approach for economic
partnership is becoming important. There is much room for further improvement of the bilateral
relationship between Japan and Malaysia. The Japan-Malaysia Economic Partnership Agreement
(JMEPA) is a strategic partnership for forging closer economic relations in trade and investment,
between the two countries. This agreement flooded Japanese FDI into Malaysia during the
second half of 2006 and it showed a positive impact from the agreement. During the last eight
years, the Malaysia-Japan Economic Partnership investment initiative facilitated active
discussion and cooperation on ways to improve the climate for Foreign Direct Investment (FDI)
in Malaysia and Japan. Foreign investment in Malaysia has risen steadily in recent years as
mentioned in this previous discussion.
Currently, the impact of FDI on the economy and technology of the host country has
caught the attention of international researchers. The reason for developing countries, such as
Malaysia, attraction to FDI was to bring technology overspill effects through demonstration,
imitation, reverse engineering, individual contact, diffusion of management skills, and the
exploitation of the international market. This can shrink the gap in higher technology within
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developed countries, to upgrade industrial technology acceleration, and to raise technology
indentations during the course of development (Chen & Chen, 2009).
Even though the background is as such, we only have a little knowledge and a few
relevant empirical researches on foreign companies in Malaysia. When Malaysia makes it much
easier for foreign companies to enter the country, and also when foreign companies respond to
that in an encouraging manner, it is strategically important and useful to know more about them.
While it is essential to develop more alternative models, theories, and frameworks, it is worth
having more empirical research, in order to understand how the system functions in the market.
2.
Theoretical Background
Various approaches are usually taken when analysing advantages, entry mode, and
performance. Cespedes & Hoshino (2001) used two different approaches to examine entry mode.
Firstly, a transaction cost model that is used to explain the relationship between entry mode and
the performance attained by the subsidiary. Secondly, an eclectic paradigm that clarifies how the
advantages of the parent company determine the entry mode selection. Recently, some scholars
have also introduced Institutional Theory (IT) to explore the entry mode decision.
In past researches, entry mode studies were investigated, mainly base on transaction cost
theory (Cespedes & Hoshino, 2001; Chen, Yang, Hsu, & Wang, 2009; Andersson & Gatignon,
1986; Palenzuela & Bobillo, 1999). The transaction cost model offers powerful insights into the
7
evolution of the MNCs. Research by (Nicholas, 1987) found that the transaction cost factors
were important determinants of the decision to invest in subsidiary’s, by pre-1939 British
manufacturing multinationals. Firms were expected to choose to enter a foreign market, only if it
offered a high risk adjusted return on investment. Therefore, transactional cost theory is an
appropriate methodology for modelling dynamic growth.
The content and predictions of the eclectic (or OLI) paradigm, are firmly embedded in a
number of different economic and business theories. The OLI paradigm holds three kinds of
advantages that shape the determination of entering a foreign market, for instance ownership (O)
advantages, location (L) advantages, and internalization (I) advantages (Dunning, 2000). The
first, ownership advantages, refers to the possession of superior intangible and tangible assets
(asset power) and skills, such as MNCs experience, firm size, and an ability to develop product
differentiation. The second sub-paradigm of the OLI tripod, offers a framework for evaluating
alternative ways in which firms may organize the creation and exploitation of their core
competencies; given the locational attractions of different countries or regions. Finally, the third
is the internationalization advantages, which stand for the benefits of internalizing foreign
activities, such as avoiding the dissipation of knowledge, preventing deterioration in the quality
of products, and eliminating the costs of writing and enforcing contracts.
8
Previous researchers define institutions, as the ‘rules of the game’, including the laws and
regulations of the host country (Daviz, Desai, & Francis, 2000; Oliver, 1997; North, 1990). The
institutional theory considers the processes by which structures, including schemas, rules, norms,
and routines, become established as authoritative guidelines for social behaviour (Scott, 2004).
Entry mode choices that can be explained by an extended transaction costs model, including
institutional and cultural variables, lead to better performance after entry; compared to those that
cannot be explained by the model (Brouthers, 2002).
3. Hypothesis development
According to Mansour & Hoshino (2001), in order to compete with host firms in their
own markets, MNCs subsidiaries must possess superior assets and skills, reflected by their size,
multinational experience, managerial expediency, etc. On the other hand, investments in R&D
are also important to any firm, because they help to develop technological capabilities, and
improve the firm’s competitive advantage and performance (Helfat, 2000 and Kotabe et al.,
2002). Therefore, all of these factors may facilitate MNCs subsidiaries to enjoy the advantages
that help them compete against domestic firms.
Previous researches put a lot effort into identifying the variables associated with firm
performance (Un & Cuervo-Cazurra, 2008; Kumarasinghe & Hoshino, 2008; Ben Youssef &
9
Hoshino, 2007; Brouthers, 2002; Mansour & Hoshino, 2001; Nitsch, Beamish, & Makino, 1996;
Woodcock, Beamish, & Makino, 1994). However, a subsidiary’s performance can be measured
in many different ways. Therefore, this research will investigate MNCs subsidiary’s performance
in foreign markets, and explain several key factors.
3.1. Entry Mode
Entry mode is one of the most crucial parts of the decision making process faced by
MNCs, in order to go abroad through FDI. There were various methods of entry mode available
i.e., wholly owned or joint venture. All of these methods involve a higher resource commitment
and a higher control (Hill, Hwang, & Kim, 1990). Research by Ogasavara & Hoshino (2007)
found that Japanese-Japanese joint ventures, with a partner that had previous experience in the
local market, performed better than wholly owned subsidiaries and traditional international joint
ventures.
Furthermore, in Yoshihara (1994) research on foreign firms in Japan, he used five scale
(highly successful, successful, doubtful, unsuccessful, highly unsuccessful) self-assessed
questionnaires to compare the profitability of sole ownership and joint ventures. The results
revealed that joint venture had statistically significant results of higher profitability than sole
ownership firms did. Hoshino & Takabayashi (1998) investigated on 182 foreign manufacturing
10
firms in Japan between 1994 and 1995. They also found that joint ventures had significantly
higher performance compared to sole ownership firms in all aspects of majority-owned, equallyowned and minority-owned joint ventures.
According to Oswald & Jahera (1991), there is a significant relationship between
ownership and performance. Their results showed that higher excess returns for a firm, are
contributed to by a higher level of inside ownership.
Drawing on the findings of these earlier studies, here is the first hypothesis:

Hypothesis 1: MNCs subsidiaries, entering through wholly owned investments,
are more likely to perform better than those entering through joint venture.
3.2. Dimensional Aspects
Previous literature shows that MNCs performance can be determined by many different
factors. Besides entry mode, dimensional aspect and international experience were other factors
that are considered in this research. Past researches have shown that the size of a firm has an
important effect on the subsidiary’s performance (Mansour & Hoshino, 2001; Isobe, 1998;
Freeman, Carroll, & Hannan, 1983). These dimensional aspects are measured by the parent
equity ratio, Return on Equity (ROE), net sales per employees, profit to net sales, Research and
Development (R&D) to net sales, depreciation expenditure to net sales and parent growth
11
average. However, the study on the factors influencing the performance of Japanese FDI in
Thailand, found that firm size is negatively associated with profitability (Siripaisalpipat &
Hoshino, 2000). Therefore, here is the second hypothesis:

Hypothesis 2: The larger the MNCs, the better the subsidiary’s performance.
3.3. International Experience
International experience increases the possibility of firms to commit large amounts of
resources to foreign a market (Medcof, 2001). On the other hand, international experience
provided firms with important knowledge about customers, markets, cultures, and governments,
which encourages future expansion (Hill, Hwang, & Kim, 1990). Numerous studies have
suggested that a firm’s internationalization experience plays an important role in the decision of
entry mode and the firm’s performance (Mathews, 2002; Siripaisalpipat & Hoshino, 2000; Li,
1995; Ramaswamy, 1993). As recommended by Cui et al., (2006) this research will also look
into the length of MNCs and subsidiary’s relationship, in order to achieve clarity for this study.
Thus, the subsidiary’s age, parent’s overseas sales to net sales and logarithm of parent overseas
sales ware used as a proxy for international experience. The following hypothesis is therefore
expected:
12

Hypothesis 3: The greater the international experience of MNCs, the better the
performance of their subsidiary.
Figure 1 illustrates the specific interrelatedness of the four main variables of the firm
performance model. These core variables are entry mode, dimensional aspects, international
experience, and subsidiary performance.
Insert Figure 1 about here
The direct investment of MNCs may bring precious resources including capital, technology,
management skills, R&D capabilities, and a network of international trade (Chen & Chen, 2009).
As MNCs expand into new markets, their success is partially determined by the ability to transfer
competitive technologies to local subsidiaries (Chung, 2001; Chen, 1996). As MNCs subsidiaries
reside in increasingly diverse environmental contexts, examining the performance of MNCs
subsidiary’s performance, compared to their parent company, becomes more and more
important. Despite the growing interest amongst scholars and the business community, there is a
lack of research on MNCs subsidiary’s performance, using parent financial analysis.
To date, extensive research on the effects of FDI has not provided a clear and conclusive
picture on the impact of Japanese firms on the local host economies. Whereas, some studies
seem to conclude that FDI has played an important role in a host country’s development, and
13
others do not (Giroud, 2000). According to Kumarasinghe & Hoshino (2008), there is still
insufficient research on Japanese MNCs activities in the Pacific region. In the case of Malaysia,
Japanese MNCs have emerged as leading direct investments in Malaysia, with RM32.1 billion
and RM33.7 billion in the years 2003 and 2004, respectively (Department of Statistics, 2008).
Numerous studies have reported literally on FDI (Chen & Chen, 2009; Kumarasinghe &
Hoshino, 2008; Ben Youssef & Hoshino, 2007; Pak & Park, 2005; Giroud, 2000; Siripaisalpipat
& Hoshino, 2000). However, it seems that very few have reported in the context of MNCs
subsidiary’s performance, comparing two different data analyses in a developing country.
Thus, it is crucial to examine the performance of Japanese MNCs subsidiaries in a host
country, in order to retain investment, and at the same time, enhance the regional competitive
advantages. Furthermore, this research attempts to determine the critical factors that contribute to
MNCs subsidiary’s performance.
4. Methodology
This study examines the relationship between entry mode, dimensional aspect, the
international experience of Japanese companies, and the attained performance of their
subsidiaries. The data analysis used the subsidiary's performance as a dependent variable and
other different characteristics of the parent company and subsidiaries, as proxies for the
14
independent variables. A multiple regression model was applied in this research and suggested
focus on performance amongst the selected MNCs subsidiaries.
4.1. Data Collection
The data for entry mode and the subsidiary’s performance was derived from Tokyo Keizai
Inc., Japan Overseas Investments, listed by countries (Toyo Keizai Inc, 2005-2009)
with
approximately 270 cases. The classification of entry modes is based on the percentage of share
ownership of the major shareholders, as reported in this database. Firms with over 95%
ownership were considered as wholly ownership subsidiaries and 20% to 94% owned firms were
considered as joint subsidiaries. Within joint subsidiaries, 51% to 94% were sub-categorize as
majority-owned joint subsidiaries, 50% as equally owned joint subsidiaries, and 20% to 49% as
minority-owned joint subsidiaries. Kamei (1996) and Yamazaki and Takeda (1992) indicated
that it is appropriate to consider 95% of ownership as wholly-ownership. Therefore, to
distinguish wholly ownership and partnership 95% ownership has been used in this research too.
Performance data for the parent MNCs was obtained from two Japanese databases, using
the year 2005 as the based year. The performance data was derived from the Nikkei Zaimu
Database (Nikkei Inc., 2005) and eol DB Tower online services (financial report).
15
4.2. Sample
Malaysia, as a single geographical area, was chosen for the purpose of this analysis. This
selection was made based on the large number of MNCs subsidiaries available and the
diplomatic relationships between Japan and Malaysia that were established in 1957. Table 2
indicates the number of Japanese MNCs subsidiaries in Malaysia from the year 2005 until 2009.
However, the amount of available data was less than expected, after eliminating missing data.
Insert Table 2 about here
4.3. Dependent variable
Firstly, growth sales ratio was used as a proxy for profitability. Since the subsidiaries growth
sales ratio represent the profit earned during a certain period, it assumed that it would be a
suitable gauge to measure the integrated profitability of that firm. From the published sales data
of the sample firms, sales growth was calculated. The subsidiaries growth sales for the sample
calculated as follows.
Subsidiaries sales growth =
(Sales amount of current year – Sales amount of previous year)
Sales amount of previous year
For the analysis, simultaneous analysis of several groups was used using SPSS for Windows
18.0 software.
16
4.4. Independent variables
This research consists of fourteen independent variables, which come from subsidiaries
and parent data. The subsidiary’s data includes subsidiary age, financial capital and sales, On the
other hand, the parent’s data takes account of the parent’s overseas sales, average age and
profitability ratio. Since the distribution of monetary values do not usually follow the normal
distribution curve, the use of the ‘natural logarithm’ of the quantity is applied, instead of the
monetary value itself, to smooth the values and bring them closer to the normal distribution (Yui,
1989). Thus, in this research parent overseas sales were computed by the logarithm to bring the
variables closer to a normal distribution.
5. Data Analysis
5.1. A descriptive comparison of the samples
In comparing some of the descriptive statistics of the sample from Malaysia, some facts
are worthy of mention. Malaysia, with 735 manufacturing subsidiaries and 686 nonmanufacturing subsidiaries, is well balanced with a nearly equal percentage. The main activities
of manufacturing subsidiaries, is machinery and transport equipment at RM38.38 billion, whilst
manufacturing goods at RM14.03 billion. According to (Cespedes & Hoshino, 2001), Japanese
companies establish subsidiary’s in developing countries, to carry out their production activities,
to sell their products, and to offer after sales services. In terms of entry mode for Japan MNCs
17
subsidiary’s into Malaysia, more than 55% were joint-venture ownerships, while the rest were
wholly owned.
5.2. Testing for the differences between entry mode and a firm’s performance
In this research, classification of performance was measured by calculating the sales
growth as the indicator for firm’s performance. The t-tests analysis employed to determine if a
statistically significant different existed between ownership and performance. t-test is used to see
whether variances vary in different groups. Therefore, if the t- test is significant at p ≤ 0.05,
confidence can be gained in the hypothesis that the variances are significantly different and that
the assumption of homogeneity of variances has been violated.
Table 3 shows the results for the performance and entry mode classification. Based on
these findings, the two-tailed value of p is 0.504 and 0.032 for manufacturing and nonmanufacturing companies respectively. The p value, for manufacturing companies is greater than
0.05 and as for non-manufacturing companies is smaller than 0.05. Therefore, this does not
indicate a significant value for manufacturing companies and have significant differences for
non-manufacturing sectors. Therefore, we must conclude that there was a significant different
between the means of ownership and the Japanese subsidiary’s performance for nonmanufacturing companies and the result was contrary for manufacturing companies. In other
words, entry mode does not have any impact on MNCs subsidiary performance for
18
manufacturing companies. Hence, the first hypothesis that stated, “MNCs subsidiary’s entering
through wholly owned investments are more likely to perform better than those entering through
joint venture” is rejected for manufacturing companies and supported for non-manufacturing
companies.
Insert Table 3 about here
This result is similar to (Mansour & Hoshino, 2001) but contradictory to several past
researches (Oswald & Jahera, 1991; Woodcock, Beamish, & Makino, 1994; Nitsch, Beamish, &
Makino, 1996). It also shows that there was no consistent association between entry mode and
financial performance.
5.3. Correlations analysis
There are two types of correlations, known as bivariate and partial. A bivariate correlation is
used between two variables, whereas a partial correlation looks at the relationship between two
variables while ‘controlling’ the effect of one or more additional variables (Field, 2009). In this
case, we employed bivariate correlation with Kendall’s tau correlation coefficient, which is
suitable for interval data and nonparametric data.
Table 4 and Table 5 show the correlation between the independent variables. This table
gives details about the correlations between the independent variables, where each of the
variables is correlated with one another. The main conclusions are discussed below.
19
The variables “Parent overseas sales” shows a high correlation with ‘Overseas sales
ratio’, ‘Subsidiary’s capital’, ‘Local and Japanese workers’, and other parent’s profitability ratio
such as ‘ROE’, ‘Equity ratio’, ‘Capital expenditure to Net sales’ and ‘Overseas sales to Net sales
ratio’. On the other hands, the ‘Subsidiary local workers’ shows a high correlation with ‘Parent
overseas sales ratio’, ‘Subsidiary age’, ‘R&D to net sales’, ‘Subsidiary sales’, ‘Subsidiary
capital’, ‘Japanese workers’ and also ‘Parent’s profitability ratio’. As mentioned by Griswold
(2009), a successful company operating in a favourable business will tend to expend employment
at both domestic and overseas operations.
Insert Table 4 and Table 5 about here
‘Subsidiary sales’ shows a correlation with ‘Japanese workers’, ‘Parent overseas sales
ratio’, ‘Subsidiary age’, ‘Parent average age’, and parent profitability ratio. According to Ittnera,
Larckera, & Randallb (2003), sales growth and return on assets are associated with strategic
performance measurement.
‘Subsidiary capital’, ‘Parent overseas sales ratio,’ and ‘Japanese workers’ are correlated.
According to (Griswold, 2009), a study from the National Bureau of Economic Research in
2005, found that during the 1980s and the 1990s, there was a strong positive correlation between
domestic and foreign growth rates of multinational firms. Desai, Foley, & Hines (2008) analyse
of US MNCs subsidiaries and parent companies, found that a 10% increase in capital investment
20
was associated with a 2.2% increase in domestic investment by the same company, including a
positive connection between parent and subsidiary sales, assets, and number of employees.
‘Parent average age’, ‘Parent equity ratio’, ‘Parent net profit ratio’ and ‘Japanese
workers’ are correlated. According to Woodcock, Beamish & Makino (1994), there was a
relationship between age and firm performance, with differences existing between established
and new ventures.
5.4. Multiple regression
Multiple linear regression models with one dependent Y variables:
Y = i +Xb + e
Where Y = a vector containing observed scores on the dependent variable;
i = a vector 1
X = a matrix of continuously distributed or categorical (dummy-coded) independent
variables
b = the vector of regression weights
e = the vector of residual or error or leftover scoring unexplained by the model
Multiple regressions applied for each of the independent variables, in order to determine
the significance of their effect on subsidiary performance and to test if the sign of their
correlation followed the hypothesis outcome. According to Makino and Delios (1996), a positive
sign for a regression coefficient indicates that the variable increases the likelihood of higher
performance, while a negative sign indicates an increase in the likelihood of lower performance.
21
The hypothesized signs and the results of the multiple regression are shown in Table 6. The main
findings are discussed below.
Insert Table 6 about here
In the case of Malaysia, the dimensional aspect, in terms of the parent’s growth revenue
average (B =2947.04) has a positive sign and is significant for manufacturing companies in years
2005 to 2009. Moreover, subsidiary local workers (B =23409.96) indicate positive value and
significant for non-manufacturing companies. This provides support for hypothesis 2, which
stated that the larger the MNCs, the better the subsidiary performance. This result is consistent to
the findings by (Mansour & Hoshino, 2001; Isobe, 1998; Freeman, Carroll, & Hannan, 1983). It
seems that, the large size of the investor is a significant predictor of good performance, when the
other variables are taken into account. In addition, the parent’s profit to net sales (B = - 1535.64)
and parent’s growth revenue Year on Year (YOY) (B = - 533.338) indicates a negative value and
significant result with p at less than .05. The negative value in this finding indicates that an
increase in the parent’s profit to net sales and parent’s growth revenue YOY by one standard
deviation may reduce the subsidiary performance.
Our results shows that the degree of international experience, measured by parent’s
overseas sales has a negative value and significant effect on subsidiary performance for years
2005 to 2009 (B = - 25464.706) for non-manufacturing companies and no significant effect for
22
manufacturing companies. According to Ajami et al., (2006), the objectives of the parent
company is also affected the subsidiary’s performance. Therefore, when parent company decided
to increased their overseas sales, this decision may benefits an MNC in the aggregate but reduce
the subsidiary’s performance. Therefore, we can conclude that there was a negative correlation
between parent’s overseas sales and subsidiary performance and therefore we have to reject the
third hypothesis.
6. Conclusion
FDIs require a business relationship between a parent company and its associated foreign
subsidiary. In order to sustain competitiveness in the foreign market, it is essential for companies
to have enough resources and flexibility, while deciding which mode of entry to use for
penetration of the foreign market. This study examines the relationship between internalization
advantages of Japanese parent companies and the attained performance of their subsidiaries.
Based on the information contained in ‘Toyo Keizai Inc. Data Bank 2005-2009’ and ‘eol DB
Tower services (financial report)’, we selected approximately 270 cases to determine the
relationship between entry mode, dimensional aspects, and international experience with
subsidiary performance.
The subsidiary's performance, as dependent variable, was measured using subsidiary’s
sales growth. While, fourteen different characteristics of the parent and subsidiary companies
23
were used as proxies for independent variables. A multiple regression model was applied in this
research. As a preliminary step to the application, we used correlation analysis to identify any
correlations amongst the independent variables that could threaten the stability of the regression
model. Six out of fourteen of the independent variables were significant with subsidiary
performance in the case of Malaysia. The six significant variables were ‘parent’s overseas sales’,
‘parent’s growth revenue average’, ‘parent’s growth revenue YOY’, ‘parent profit to net sales’,
'parent’s capital expenditure to net sales’ and ‘subsidiary local workers’, with a p value less than
0.05 and associated with subsidiary performance.
The relationship between ownership and a firm’s performance was an important issue and
has been an on-going discussion in corporate finance literature since the classic work of (Berle &
Means, 1932). They suggested an inverse relationship between the divergence of ownership and
firm performance. Previous researches, using various methodologies, have focused on the
relationship between ownership and firm’s performance with mixed findings. A study conducted
by (Oswald & Jahera, 1991; Mehran, 1995; Holthausen & Larcker, 1996) found a positive
relationship between ownership and performance. Their findings showed that entry mode has a
significant relationship with firm performance (Oswald & Jahera, 1991). In this paper, we used ttest to analyse the relationship between entry mode and firm’s performance. However, none of
the results revealed a statistically significant relationship between these two variables. Our
24
insignificant findings have a similar result to (Mansour & Hoshino, 2001; Cespedes & Hoshino,
2001). Therefore, these findings rejected the first hypothesis.
Besides, this research shows that dimensional aspects, such as parent’s growth revenue
average and subsidiary local workers have a positive effect on performance in line with
(Mansour & Hoshino, 2001; Konopaske, Werner, & Neupert, 2002). Moreover, in this paper we
also consider the effect of international experience on performance. Parent’s overseas sale was
found negatively significant to the subsidiary performance. Thus, these findings support both the
second and the reject the third hypotheses in this research.
However, the study also has several limitations. One limitation is that only the
subsidiaries sales growth from each subsidiary was used as the proxy for the profitability in
foreign subsidiaries upon conditions for using these company data. Normally, it is more desirable
to include several indicators to measure more accurate profitability of a business. Moreover, it is
believed that the objectives of entering into Japan can be assessed by incorporating self-assessed
questionnaire such as Woodcock et al. (1994); Nitsch et al. (1996) to inquire on financial
profitability which cannot be investigated wholly by using finance data. Hence, it would be
interesting to combine actual financial data and self-assessment questionnaire completed by the
foreign subsidiaries in Japan and conduct some analyses. Future research should look into this
aspect.
25
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Figure 1: Conceptual Framework
Independent Variables
Dependent Variables
FDI Entry mode
- Wholly owned subsidiaries
- Joint Venture
Dimensional Aspect
- Size of parent company
i. Parent Profit/ Net Sales
ii. Parent Average Age
MNCs Subsidiary’s
iii. Parent Recurring Profit/Employees
Performance
iv. Parent Fix Asset Turnover
v. Parent Capital Expenditure/Net Sales
vi. Parent Growth Revenue Average
vii. Parent Growth Revenue YoY
- Size of subsidiary company
i. Subsidiary Capital
ii. Subsidiary Local Workers
International Experience
- Subsidiary Age
- Parent Overseas Sales
- Parent Overseas Sales/Net sales
31
Table 1: Foreign Direct Investment Statistics in Malaysia
Country
Composition ratio
2006
2007
2008
2009
Amount
(Million RM)
6523
Amount
(Million RM)
5595
Amount
(Million RM)
7041
Japan
31.8
Amount
(Million RM)
4412
China
24.7
1885
2952
119
5478
United States
10.6
2477
3020
8669
2345
20228
33426
46099
22145
Total(Inc. Others)
Source: JETRO (2010)
Table 2: No. of Samples from 2005-2009
Year
No. of Japanese MNCs Subsidiaries in Malaysia
No. of Available Japanese MNCs Subsidiaries
2005
803
60
2006
771
58
2007
779
50
2008
759
59
2009
753
43
Table 3: Performance Breakdown by Entry Mode
Performance
Ownership
Wholly
Joint
Venture
Totals
Sig.
t
df
Manufacturing
Service
N
78
Mean
16667.00
N
36
Mean
36113.15
92
20716.18
55
16366.60
170
91
0.504
-0.670
168
0.032
2.184
89
32
Table 4: Correlation Matrix of Independent Variables for Manufacturing
Table 4: Correlation Matrix of Independent Variables for Manufacturing
Unit
Measurement
Variables
1
Subsidiary Japanese Workers Correlation Coefficient
2
Parent Overseas Sales Ratio
Sig. (2-tailed)
3
Parent ROE
4
Parent Net Profit Ratio
5
Parent Equity Ratio
Parent Average Age
Subsidiary Age
8
Parent Profit to Net Sale
10
11
12
Parent Capital Expenditure to
Sales
Sig. (2-tailed)
Parent Growth Revenue
Average
Correlation Coefficient
Parent Growth Revenue YOY
Correlation Coefficient
Sig. (2-tailed)
Parent Fix Assets Turnover
14
15
Parent Depreciation
Expenditure to Net Sales
Correlation Coefficient
Parent Net Sales/ Employees
Correlation Coefficient
Sig. (2-tailed)
Sig. (2-tailed)
16
Parent Recurring profit/
17
Employees
Parent Overseas Sales to
Net Sales Ratio
18
Parent No. of Consolidate
Sig. (2-tailed)
Sig. (2-tailed)
Subsidiary Capital
Subsidiary Sales
21
Subsidiary Local Workers
Parent Overseas Sales
Ratio
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Ratio
Ratio
Ratio
*
.033
**
Ratio
Correlation Coefficient
Correlation Coefficient
*
-.106
-.169
.
**
-.356
**
1.000
.071
.061
.018
-.021
.075
.206
.231
.247
.726
.695
.174
.096
-.021
.103
.703
**
.009
*
.021
*
.139
.016
**
.000
.001
.199
.000
.070
.063
.099
.215
.275
.053
.098
.101
.084
.081
.017
.186
**
.285
.000
**
**
-.312
.001
.000
.009
-.106
.878
.066
**
.004
.000
**
.000
**
.000
.004
.293
**
**
**
.001
.984
-.089
.058
.080
.256
.042
.024
.411
.644
**
.114
.470
.252
.154
**
**
**
*
-.122
*
1.000
**
.207
.121
.913
.000
**
.
.006
.026
.041
.245
.446
.000
-.033
.047
.
.311
.540
.387
.099
-.079
.018
-.032
.055
.142
.732
.551
.004
-.087
-.024
.111
.635
**
**
.015
**
.001
**
.004
.140
-.171
.202
.007
.111
**
.215
.011
-.210
**
-.221
**
.149
**
**
.179
.
**
**
**
.000
-.017
**
-.213
.000
**
.023
.882
.000
.071
.106
.105
1.000
.000
.001
.516
**
.340
**
-.182
.073
.495
1.000
.
.062
.236
.747
-.008
**
.001
.154
.000
*
-.121
-.193
1.000
.000
.000
.000
.845
*
-.020
.709
.000
**
*
.129
.122
.000
-.147
-.083
**
.000
.026
.215
.065
-.243
1.000
.677
.000
.002
**
-.211
-.023
.003
-.162
.000
*
**
.000
.001
**
.040
.000
.000
.176
.329
.
*
-.117
*
.107
.041
.054
.731
.294
**
.159
1.000
.
.044
-.337
.002
.395
.000
.063
.049
.015
.230
.344
.769
**
.245
.000
**
.192
.
-.018
**
.213
.168
**
**
-.103
.001
.045
.056
.101
.074
.244
.049
.000
.221
.066
.062
.001
.000
.320
-.011
.023
.046
.039
-.104
.066
.054
.098
-.068
-.003
.020
.864
.715
.458
.543
.106
.304
.387
.117
.288
.966
.000
.108
-.053
-.077
.103
-.016
-.004
.006
.067
.312
.139
.058
.769
.936
.908
.079
.053
.129
.160
.332
.018
-.057
-.036
.101
.315
.522
.072
*
**
.171
.005
.225
**
.000
**
**
.001
**
**
1.000
.042
-.160
**
.179
.242
.
.000
.000
.000
**
.969
.871
.000
.409
.000
.453
**
.096
.000
*
.047
.068
**
.225
*
.108
.000
**
.195
.611
.744
.180
Million RM
**
1.000
.000
.073
.397
Individuals
.850
**
.000
.308
Million RM
.321
.001
.258
Million RM
.
.010
.047
-.051
Companies
*
.000
.178
Ratio
1.000
.000
.114
-.214
**
.010
-.182
Ratio
.520
.048
.134
Ratio
1.000
.
.103
.073
.019
Correlation Coefficient
Sig. (2-tailed)
.014
.241
Ratio
**
.003
.130
Correlation Coefficient
Sig. (2-tailed)
22
Ratio
Correlation Coefficient
Sig. (2-tailed)
4
.
*
.157
Correlation Coefficient
Sig. (2-tailed)
20
Years
Correlation Coefficient
Sig. (2-tailed)
19
Years
Correlation Coefficient
Sig. (2-tailed)
.169
.004
-.151
Correlation Coefficient
Sig. (2-tailed)
13
Ratio
Correlation Coefficient
Sig. (2-tailed)
**
.119
Parent R&D to Net Sales Ratio Correlation Coefficient
Sig. (2-tailed)
9
Ratio
Correlation Coefficient
Sig. (2-tailed)
1.000
.137
Correlation Coefficient
Sig. (2-tailed)
7
Ratio
**
.006
.160
Correlation Coefficient
Sig. (2-tailed)
6
Ratio
Correlation Coefficient
Sig. (2-tailed)
3
.
.173
Correlation Coefficient
Sig. (2-tailed)
2
Individuals
Correlation Coefficient
Sig. (2-tailed)
1
1.000
.383
.000
**
.165
-.148
.004
**
.002
.028
.610
**
-.123
*
.023
.112
.048
*
.132
.014
*
**
.347
.000
.061
-.119
.278
.024
.014
.033
.808
.540
.084
-.005
.018
-.078
.127
.929
.740
.176
.000
.046
.505
.072
.061
-.058
.020
.232
.304
.329
.732
.142
.013
*
.061
.286
-.127
.028
*
**. Correlation is significant at the 0.01 level (2-tailed).
33
.310
**
.118
*
.037
*
**
.183
.001
**
.166
.003
.207
**
.000
.137
.019
*
.208
.000
**
.126
.029
-.241
*
.147
.011
1.000
.
**
-.220
1.000
.000
*
.
-.020
.692
*
-.136
.000
.016
.027
-.042
.070
.664
.497
.264
**
.000
.146
.188
**
.006
-.119
**
**
-.357
.
*
.003
.961
**
-.160
.000
.004
.050
.046
.384
.421
*
1.000
.012
**
-.165
1.000
-.167
.002
.029
.001
.159
**
-.178
.001
.007
*
.
**
-.329
.000
.201
*
1.000
.000
**
.254
**
**
.413
.
.112
.090
.052
.159
.184
**
.002
**
.209
.760
**
.001
.380
.000
-.020
.018
.789
**
-.009
.895
1.000
.
.389
**
1.000
.000
.345
.
**
.000
.146
.013
.461
**
1.000
**
.122
.000
*
.274
.000
.
.049
*
1.000
.
Table 5: Correlation Matrix of Independent Variables for Services
Variables
Unit
Measurement
1
2
3
4
5
6
7
8
9
1
Parent Recurring
Profit/Employees
Correlation Coefficient
2
Overseas Sales to
Net Sales Ratio
Correlation Coefficient
.063
Sig. (2-tailed)
.475
.
Parent No. of
Consolidate
Correlation Coefficient
-.040
.119
.663
.233
.
Subsidiary Capital
Correlation Coefficient
-.308 **
.009
-.067
.000
.923
.488
.
-.298 **
.016
.032
.258 **
.001
.873
.751
.002
.
-.209 *
-.008
.033
.259 **
.286 **
.015
.931
.732
.001
.001
.
.054
.350 **
.240 *
.093
.159
.202 *
.538
.000
.015
.299
.096
.022
.
-.364 **
-.073
.024
.322 **
.279 **
.299 **
.005
.000
.462
.813
.000
.002
.000
.960
.
3
4
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
5
Subsidiary Sales
6
7
8
9
10
16
17
18
19
20
21
22
16
17
18
19
20
21
22
Ratio
Companies
Million RM
Million RM
1.000
1.000
1.000
1.000
Subsidiary Japenese
Workers
Correlation Coefficient
Parent Overseas
Sales Ratio
Correlation Coefficient
.008
.986 **
.105
-.040
-.049
-.051
.304 **
-.011
Sig. (2-tailed)
.926
.000
.289
.657
.613
.571
.000
.910
.
Parent ROE
Correlation Coefficient
.473 **
-.036
-.133
-.200 **
-.077
-.075
.082
-.172 *
-.024
.000
.688
.146
.008
.341
.332
.336
.033
.781
**
.074
-.189
*
-.149
*
.067
.000
.403
.039
.046
.043
.056
.001
.043
.438
.000
.
-.042
.156
-.021
-.027
-.096
-.084
-.355 **
-.040
.111
-.192 **
.355 **
.602
.078
.817
.730
.242
.276
.000
.626
.194
.008
.000
.
-.128
.184 *
.210 *
.034
.099
.026
.249 **
.043
.117
-.065
-.189 *
-.358 **
.136
.050
.030
.672
.242
.746
.005
.612
.197
.386
.013
.000
.
-.089
.037
.107
.007
.402 **
.088
.251 **
.033
.126
.161 *
-.111
-.381 **
.342 **
.288
.686
.258
.926
.000
.266
.004
.689
.153
.029
.134
.000
.000
.
-.126
.138
.185
.026
-.053
.124
.176
.006
.306
*
-.107
.098
.164
-.068
.012
.272
.284
.138
.827
.664
.313
.175
.965
.019
.353
.395
.154
.569
.916
.
.333 **
.092
-.162
-.148
-.267 **
-.184 *
-.264 **
-.171
.099
.260 **
.968 **
.337 **
-.112
-.163
.117
.000
.301
.076
.088
.003
.032
.003
.060
.265
.001
.000
.000
.194
.051
.308
.
-.065
.107
-.073
.019
-.065
.086
.052
-.044
.174
-.110
.174 *
.134
.076
-.022
.459 **
.198 *
.451
.259
.455
.835
.512
.354
.581
.653
.068
.204
.045
.122
.409
.807
.000
.022
.
.271 **
.191 *
-.184 *
-.026
-.066
.055
-.029
.017
.164
.203 *
.235 **
.049
-.125
-.123
.105
.242 **
.128
.001
.032
.045
.767
.470
.529
.745
.854
.067
.013
.004
.546
.147
.145
.360
.003
.143
.153
.051
-.093
.070
-.027
.121
.073
.035
.001
.135
.019
-.093
-.106
.038
.081
.025
-.073
.059
.566
.311
.420
.767
.159
.408
.701
.995
.095
.819
.252
.216
.650
.480
.754
.396
.000
.
.145
-.103
.013
-.154
.030
-.083
.076
-.067
-.092
.284 **
-.242 **
-.342 **
-.037
.170 *
-.273 *
-.269 **
-.580 **
-.040
-.018
.074
.248
.883
.075
.746
.336
.390
.463
.301
.000
.003
.000
.665
.042
.018
.001
.000
.626
.827
.
-.230 **
.152
.087
.158
.030
.102
-.027
.168
.166
-.320 **
.203 *
.332 **
.055
-.131
.459 **
.228 **
.578 **
.071
-.037
-.717 **
.005
.086
.342
.068
.746
.237
.756
.066
.062
.000
.013
.000
.519
.118
.000
.005
.000
.386
.651
.000
.
.465 **
.005
.001
-.157
-.056
-.118
.276 **
-.252 **
-.052
.308 **
-.154
-.379 **
.015
.094
-.397 **
-.158
-.250 **
.025
.099
.381 **
-.515 **
1.000
.000
.959
.995
.069
.540
.169
.002
.006
.554
.000
.058
.000
.864
.262
.001
.051
.004
.757
.224
.000
.000
.
Sig. (2-tailed)
Sig. (2-tailed)
Individuals
Million RM
Individuals
Ratio
Ratio
Parent Net Profit Ratio Correlation Coefficient
Parent Equity Ratio
Parent Average Age
Subsidiary Age
.322
Ratio
Correlation Coefficient
Ratio
Correlation Coefficient
Years
Correlation Coefficient
Sig. (2-tailed)
15
15
Correlation Coefficient
Sig. (2-tailed)
14
14
Parent Overseas
Sales
Sig. (2-tailed)
Sig. (2-tailed)
13
13
Correlation Coefficient
Sig. (2-tailed)
12
12
Subsidiary Local
Workers
Sig. (2-tailed)
11
11
.
Ratio
Correlation Coefficient
Sig. (2-tailed)
10
1.000
R&D to Net Sales
Ratio
Correlation Coefficient
Parent Profit to Net
Sales
Correlation Coefficient
Parent Capital
Expenditure to Sales
Correlation Coefficient
Parent Growth
Revenue Average
Correlation Coefficient
Parent Growth
Revenue YOY
Correlation Coefficient
Parent Fix Assets
Turnover
Correlation Coefficient
Parent Depreciation
Expenditure to Net
Sales
Parent Net
Sales/Employees
Correlation Coefficient
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Years
Ratio
Ratio
Ratio
Ratio
Ratio
Ratio
Ratio
Correlation Coefficient
Sig. (2-tailed)
Ratio
*
-.153
*
-.166
1.000
1.000
-.284
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
34
**
1.000
-.166
1.000
1.000
.
.386
**
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
.
.292
**
1.000
1.000
1.000
Table 6: Multiple Regressions
Independent Variables
Included
Manufacturing
Service
Model 1
Model 2
Model 1
Model 2
39879.26
(0.731)
-11986.48
(-1.841)
27.582
(0.114)
-1535.64
(-1.742)
77.225
(0.305)
1016.20
(1.916)
-7927.84
(-1.831)
-9775.44
(-1.621)
1621.93
(1.241)
2718.90**
(3.719)
-533.338**
(-2.088)
1840.31**
(2.324)
32622.937
(0.610)
-12523.182
(-1.965)
-52.488
(-0.219)
-1466.125**
(-2.050)
381569.113**
(2.611)
-16243.23
(-1.295)
523.45
(1.637)
-3062.75
(-1.124)
-361.33
(-1.675)
-1341.12
(-1.817)
-11268.45
(2.120)
21069.49**
(9938.66)
-5687.26
(-1.790)
2707.00
(1.575)
-1116.87
(-1.582)
-800.28
(-0.531)
335201.82**
(2.273)
-25464.706**
(-2.198)
494.919
(1.508)
-4106.66
(-1.507)
F
3.265
3.377
2.092
1.913
P
0.001
0.001
0.052
0.080
R Square
0.268
0.275
0.426
0.374
Constant
1. Parent Overseas Sales
2. Parent Overseas Sales/Net Sales
3. Parent Profit/Net Sales
4. Parent Recurring Profit/Employees
5. Subsidiary Age
6. Subsidiary Capital
7. Subsidiary Local workers
8. Parent Age
9. Parent Growth Revenue Average
10. Parent Growth Revenue YOY
11. Parent Capital Expenditure / Net
sales
12. Fix Asset Turnover
956.311
(1.833)
-7848.74
(-1.826)
-10620.204
(-1.761)
1757.437
(1.391)
2947.044**
(3.864)
-546.157**
(-2.145)
2221.037**
(2.667)
2941.254
(0.996)
-1439.228
(-1.903)
-6274.67
(-0.745)
23409.961**
(2.315)
-4352.094
(-1.377)
1715.464
(1.034)
-1227.743
(-1.700)
-438.094
(-0.286)
Model Indices
**significant at the 5% level
35