joint ventures and governance

8/14/2019 Joint Ventures And Governance

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Joint Ventures Around the Globe from 1990-2000:

Forms, Types, Industries, Countries and Ownership Patterns

Sviatoslav A. Moskalev*(a)

Adelphi University

R. Bruce Swensen*

Adelphi University

Abstract:

Joint ventures (JVs) and alliances are important forms of inter-organizational cooperation becausethey allow firms to achieve complex mutual tasks, otherwise impossible using simple arms-length contracts, but without actually acquiring one another. In light of recent trends inglobalization, this feature of JVs and alliances is vital to multi-national corporations (MNCs).These firms have complex operations, making simple arms-length contracts insufficient. MNCsare also very large, so that mergers and acquisitions and takeovers are extremely expensive. Inthis paper, we describe global trends in JVs and alliances for the period 1990 to 2000, utilizingthe Thomson Financial SDC Platinum database. We survey existing theoretical and empirical

literature on JVs and alliances, and provide a detailed description of the world of JVs andalliances as depicted by this database. We report a number of interesting facts regarding theforms and types of JVs and alliances, their industry and geographic distribution, and patterns ofownership


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ownership

Introduction

Companies cooperate with one another because they believe that the cooperation can be

beneficial to them. Generally speaking, inter-organizational cooperation can take three forms: (a)

simple contracts1; (b) mergers and acquisitions (M&As) and takeovers; (c) joint ventures (JVs)

and alliances. The forms of cooperation have different consequences for the autonomy of the

parties post closing. Consequently, the parties choose their desired form of cooperation based, at

least in part, on the amount of autonomy they are willing to surrender.

The most basic form of inter-organizational cooperation is the simple contract. Examples

include customer-supplier contracts, service contracts, and distribution contracts, as well as many

others. While simple contracts can be incomplete (e.g., Hart 1995; Aghion and Tirole (1997);

Hart and Moore (1999)), their dominant feature, relative to other forms of inter-organizational

cooperation, is that they typically do not require transfer of assets and control so that the parties to

the contract remain autonomous.M&As and takeovers are the most sophisticated forms of inter-organizational

cooperation. By definition, they entail transfer of assets and control, result ing in significant

change in the autonomy of at least one of the parties. The finance literature generally proposes

synergy (e.g., Berkovitch and Narayanan (1993)), agency (e.g., Amihud and Lev (1981); Jensen

(1986); Shleifer and Vishny (1989)), and hubris (e.g., Roll (1986)) as primary motives for M&As

and takeovers.

JVs and alliances are intermediate forms of inter-organizational cooperation. JVs are

separate business entities established by the partners in order to achieve a mutual task. The


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e.g., World Bank (2002)), it is important to study JVs and alliances because they allow multi-

national corporations (MNCs) to perform complex mutual tasks, otherwise impossible with

simple arms-lengths contracts, without acquiring one another. This feature is especially

important to MNCs because their sophisticated operations often make simple arms-length

contracts insufficient, but their substantial assets make M&As and takeovers very expensive.

This paper describes global trends in JVs and alliances for the period 1990 to 2000,

utilizing the Thomson Financial SDC Platinum Alliances/Joint Ventures database. We survey

theoretical and empirical literature on JVs and alliances, and provide a detailed description of theworld of JVs and alliances as depicted by the SDC database. Our results highlight a number of

noteworthy observations related to the forms and types of JVs and alliances, their industry and

geographic distribution, and patterns of ownership.

First, we establish that JVs and alliances are flexible inter-organizational cooperative

mechanisms that allow multiple domestic and foreign partners to form business entities which

operate in single or multiple countries. While some deals include as many as twenty partners,

others have operations in as many as eighteen countries. For international cooperation, firms use

JVs more frequently than alliances; for domestic cooperation, alliances are more common. Data

on the dollar size of JVs and alliances is rarely disclosed, making qualitative judgments difficult.

Based on the relatively small number of transactions (about 7% of the dataset) that disclose dollar

size, it appears that JVs are somewhat smaller than alliances. The paper also confirms a

previously observed contraction in the frequency of JVs and alliances around the globe after

1995, which is commonly attributed to liberalization of foreign investment regimes in various

h t t i ( UNCTAD (2000) D i F l d Hi (2004))


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we show that exploration-agreement JVs have the highest industry clustering, with over 95% in

the mining and the oil and gas industries. The frequency of transactions with cross-border

participants in technology-agreement JVs is higher than in R&D-agreement JVs, indicating that

foreign partners are more likely to receive, than to jointly develop, new technology.

Fourth, we find substantial country clustering in the geographic distribution of JVs and

alliances. Of 179 countries around the globe, only seven countries accounted for 63.4% of global

JVs and alliances. In addition, we provide evidence on the geographic distribution of the various

types of JVs and alliances.Lastly, we study ownership patterns in JVs and alliances. We present evidence on the

amount of partners equity stakes in JVs and alliances, and the frequency of equal ownership.

Our results corroborate existing evidence (e.g., Hauswald and Hege (2004)) that partners in JVs

and alliances have a preference for equal ownership, and we extend the literature by showing that

this phenomenon holds internationally and for multiple-partner JVs and alliances.

The paper is organized as follows. First, we review the theoretical and empirical

literature on JVs and alliances. Second, we discuss the data. Third, we present our results.

Lastly, we conclude and propose avenues for future research.

Review of the Theoretical Literature on JVs

The transactions costs theory (TCT) and the property rights theory (PRT) establish the

theoretical framework for understanding JVs. The TCT, developed by Klein, Crawford and

Alchian (1978), and others, emphasizes that, as assets become more specific, potential gains from

t i ti b h i b t di t i F th t ti t t i ll i


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shows that the PRTs predictions differ in important ways from those of the TCT, and that the

existing empirical evidence that is supportive of the TCT sheds little light on the empirical

relevance of the PRT. Cai (2003) extends the TCT to situations where parties can choose both

the type and level of investment. He shows that the PRT results are obtained when specific and

general investments are complementary but, when specific and general investments are

substitutes, joint ownership provides incentives to make specific investments, and can therefore

be an optimal structure.

Moral hazard issues that arise in cooperative efforts are common in JVs. Holmstrom(1982) showed that a capitalistic firm has an advantage over a partnership in resolving the free-

rider problem in teams because ownership and labor are partly separated. Legros and Matthews

(1993) build on Holmstroms work and show that, for some types of partnerships, a sharing rule

exists that can elicit an efficient set of actions. These include partnerships in which partners

actions are perfect complements (Leontief partnerships) or where one partner is not able to affect

output. They show that efficiency can be approximated to any desired degree and that free-riding

causes inefficiency only to the extent that either the partners liability is limited or partners

wealth is bounded. Vislie (1994) provides similar results, concluding that, when inputs are strict

complements(Leontief technology) free-riding can be avoided.

In the theoretical literature, optimal ownership allocation has been modeled extensively

on JVs. The results indicate that, as a consequence of various partner characteristics, optimal

ownership allocation should be asymmetric. Darrough and Stoughton (1989) analyze the impact

of private information on profit-sharing arrangements negotiated by partners in JVs. Chemla,

H bib d Lj i t (2004) d Bh tt h d L f t i (1989) t d th ff t f


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Review of the Empirical Literature on Domestic JVs

Empirical literature on domestic JVs is limited. One strand of this literature analyzes the

reaction of stock price to announcements of formation of alliances and JVs. The other addresses

issues related to allocation of control in strategic alliances between pharmaceutical and

biotechnology research companies.

A number of event studies document positive and significant announcement returns

related to formation of domestic strategic alliances and JVs. In their investigation of 136

domestic JVs between 1972 and 1979, McConnell and Nantell (1985) find significant wealthgains from JVs. Since returns to stockholders are comparable to those resulting from mergers,

the authors conclude that their results are supportive of the hypothesis that synergy is the source

of gain from corporate combinations. Chan, Kensinger, Keown and Martin (1997) report similar

results in their study of 345 strategic non-equity alliances over the period 1983-1992.

Johnson and Houston (2000) study returns generated by 119 domestic JVs, distinguishing

between horizontal and vertical transactions. They find that horizontal JVs produce synergistic

wealth gains that are shared by the parties to the JV, while vertical JVs create significantly

positive mean excess return only for suppliers. The authors conclude that vertical JVs are used

when the potential for hold-up problems is substantial and as a financing alternative for suppliers.

Allen and Phillips (2000)examine the relationship between long-term block ownership

by corporations and changes in target firms stock prices, investment policies and profitability.

They find the largest significant increases in targets performance when corporate block

ownership is accompanied by alliances, JVs, and other product market relationships between

h i d t t fi M h d N d (1998) t i ifi t iti b l


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estate JVs in his sample, and a statistically significant difference in excess returns between real

estate and non-real estate firms. The former result is consistent with the synergy hypothesis and

the latter is consistent with the informational asymmetries hypothesis. In contrast, a study by

Corgel and Rogers (1987) does not provide evidence of synergies in real estate JVs. Their

analysis of twenty-four JVs over the period 1979-1985 indicates no significant announcement

effect for real estate development JVs.

The second strand of empirical literature on domestic JVs investigates the allocation of

control in strategic alliance agreements, often between pharmaceutical and biotechnologyresearch companies. Lerner and Merges (1998) examine the determinants of control rights in

biotechnology alliances between R&D firms and larger firms with substantial financial resources

and find that increased control rights are allocated to R&D firms as their financial resources

increase. Lerner, Shane and Tsai (2003) study two hundred alliance agreements between

biotechnology firms during the period 1980-1995. They find that, when external equity financing

is readily available, alliance agreements tend to assign greater control rights to the R&D firm;

such alliances are more successful.

In a related work, Robinson (2005) develops a model that predicts firms will prefer

alliances over internal projects when the risk of the alliance activity is greater than the risk of the

firms primary activities. In support of his model, he finds that alliances tend to occur in risky,

high-tech industries, and when industries have different risk characteristics. Elfenbein and Lerner

(2003) analyze alliances involving Internet portals between 1995 and 1999 to determine the

extent to which contract theory explains the division of ownership and the allocation of control

i ht Th fi d th t i t t ith i l t t t th i hi i d t


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assets. Hennart (1991) reports that the results of his empirical study of the factors that determine

the degree of ownership by Japanese manufacturing firms in their American subsidiaries is

consistent with the TCT and with the determinants of ownership choices made by U.S firms; that

is, Japanese manufacturing investors form JVs in order to combine intermediate inputs that have

high transaction costs. Ramachandran (1993) studies the transfer of technology from developed

countries to firms in India and shows that 100%-owned subsidiaries of foreign multinationals

receive more resources than do Indian-owned firms or subsidiaries partially-owned by foreign

multinationals.The issue of resource complementarity has been empirically studied in the context of

IJVs. Balakrishan and Koza (1993) view the joint venture as an alternative to merger or

acquisition when information asymmetry about the target firms assets results in high transaction

costs for M&As. They theorize that the joint venture is an efficient mechanism for pooling

complementary assets when the parents come from dissimilar businesses. Their theory is

supported by an event study of 64 JV announcements, which demonstrates that, in general, joint

ventures create value, with abnormal returns that are significantly larger when the parents operate

in businesses with technological and managerial differences. Furthermore, abnormal returns to

acquirers and targets involved in M&As were greater when acquirer and target firms are in

similar businesses. Blomstrom and Zejan (1991), using data from Swedish multinationals, find

that firms with limited foreign production experience and diversified product lines are most likely

to choose minority ventures. Gomes-Casseres (1989) utilizes data from subsidiaries of 180 U.S.

multinationals and demonstrates that, in selecting ownership structure, multinationals choose JVs

ith h t t fi th th h ll d b idi i if th l l fi t


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subsequent liberalization of these restrictions during the 1980s. These policy changes led to

small but consistent decreases in 50-50 and minority affiliates. Henisz (2000) and Gatignon and

Anderson (1988) show that, in host countries with substantial political risk, multinationals can

reduce their risk exposure by partnering with local firms. However, as political risk increases, so

does the risk that the local firm will exploit the political system at the expense of the

multinational firm. Desai, Foley and Hines (2004) study the determinants of partialownership of

foreign affiliates by U.S. multinationals and the decreased use of joint ventures since the 1980s.

They show that 100% ownership is most frequent when firms coordinate international productionand benefit from technology transfers and worldwide tax planning. Liberalized ownership

restrictions and joint venture tax penalties imposed in 1986 led U.S. multinationals to increase use

of 100% ownership and to increase intrafirm trade and transfer of technology.

Finally, we note that a number of event studies have demonstrated that markets view IJVs

as value enhancing. Numerous papers (e.g., Lummer and McConnell (1990), Lee and Wyatt

(1990), Chen, Hu, and Shieh (1991), Etebari (1993), Crutchley, Guo, and Hansen (1991),

Janakiraman, Lambda and McKeon (1999), Prather and Min (1998), Gleason, Lee and Mathur

(2002), Irwanto, Vetter and Wingender (1999), He, Myer and Webb (1997)) document positive

and significant abnormal returns associated with IJV announcements.

Data

The data in this study are from the Thomson Financial SDC Platinum Alliances/Joint

Ventures database, which attempts to collect all worldwide JV transactions from SEC filings and

it i t ti l t t t d bli ti i d th SDC th


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Results

Summary Statistics for Joint Ventures

Table 1 shows basic summary statistics. The frequency of JV deals is summarized in

Panel A of Table 1. In total, there were 60,446 JV transactions around the globe during the 1990-

2000 period, of which 58.72% had cross-border participants and 37.48% had domestic

participants only. SDC defines JVs with cross-border participants as deals where participants

ultimate parents are not from the same nation. Domestic JVs are deals with all participants from

the same nation. This distinction is significant because domestic JVs represent internal businessactivity in a given country, while JVs with cross-border participants represent international

business cooperation. Additionally, 5,839 multi-regional JVs (9.66% of the total) occurred

during this period; these are defined by SDC as deals with activities in more than one nation.

They are created primarily to serve multiple countries, so it is not surprising that 96.35% (5,626

of 5,839) of multi-regional JVs have cross-border participants2.

While the SDC database accurately identifies the occurrence of JV deals, its description

of their dollar size is poor. Panel A of Table 1 shows that only 7.42% of all JVs (4,484 of

60,446) disclosed their estimated capitalization3 and another 7.42% disclosed their estimated

cost4. This low rate of reporting is a consequence of the fact that companies typically do not view

JVs as major corporate restructurings, and thus are not obligated to report their size. Among

those that disclose the dollar amount, some have motivations that can create selection bias. Thus,

results derived from SDCs capitalization and cost data should be viewed with caution.

Additionally, most firms that disclose information on the dollar size of JVs report either estimated

it li ti ti t d t b t t b th A di t SDC l 402 JV d l (0 67%)


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separately JVs with cross-border participants, multi-regional JVs and domestic JVs. The results

are similar, with a slightly greater tendency towards two-partner JVs among domestic JVs.

Panel C of Table 1, which reports the number of countries in which JVs operate, indicates

that 85.0% of JVs intend to operate in only one country, and 8.2% in two countries, while the

remaining deals cover as many as eighteen countries. Compared with the full sample, JVs with

cross-border participants have a somewhat greater tendency to serve two countries (12.7% versus

8.2%), primarily because they are comprised of international participants and have a broader

geographic scope. Multi-regional JVs operate primarily in two countries (90.68%), with sometransactions serving three countries (5.69%). Virtually all domestic JVs serve only one (i.e.,

domestic) country (99.93%), with a small number of unique cases serving more than one country.

Panel D of Table 1 describes the forms utilized in cooperative activities: strategic

alliances versus independent JV firms. SDC defines a strategic alliance as a cooperative

business activity, formed by two or more separate organizations for strategic purposes, which

does NOT create an independent business entity, but allocates ownership, operational

responsibilities, and financial risks and rewards to each member, while preserving each member's

separate identity/autonomy. An independent JV firm is: a cooperative business activity, formed

by two or more separate organizations for strategic purposes, which creates an INDEPENDENT

business entity, and allocates ownership, operational responsibilities, and financial risks and

rewards to each member, while preserving each member's separate identity/autonomy. The new

entity can either be newly formed or a combination of pre-existing units and/or divisions of the

members.

Th di ti ti b t th f i i ifi t b f th diff ti l


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believe this latter result is a consequence of the greater difficulty inherent in coordinating

strategic alliances with partners from different countries. This argument is supported by the data

for domestic JVs: 69.2% are formed as strategic alliances and only 30.8% as independent JV

firms. Strategic alliances are common among multi-regional JVs (64.8%), primarily because it is

more expensive to achieve multi-regional access by establishing independent JV firms in different

countries.

Panel E of Table 1 shows the dollar size of JVs. The estimated capitalization of the

median JV in the dataset is 8 million US dollars and the median estimated cost is 30 million USdollars. These medians are substantially less than the respective means (79.07 and 264.56 million

US dollars), implying that some JV transactions are very large5. On the other hand, the mean and

median estimated capitalization and cost of JVs with cross-border participants, multi-regional JVs

and domestic JVs are similar6. Strategic alliances are substantially larger than independent JV

firms. The mean and median capitalization for strategic alliances are 138.6 and 20 million US

dollars, respectively, but only 76.4 and 7.6 million US dollars, respectively, for independent JV

companies. Similar differentials are observed for estimated cost (308.4 and 25.1 million US

dollars versus 253.3 and 30 million US dollars, respectively). The finding that strategic alliances

are larger than independent JV firms supports the argument that firms commit more funds to

investment projects in strategic alliances than in independent JV firms because the former entities

have lower transaction costs.

Table 2 reports the frequency and size of JVs annually, from 1990 through 2000. The

primary finding, also apparent in Graph 1, is that frequency of JVs contracted after 1995. The

b f JV i d t dil f 1990 th h 1995 b t th f ll h l i 1996 Th


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Distribution of JVs by Industry

In this section, we discuss the industry distribution of JV deals around the globe. Tables

3 through 5 present evidence regarding the frequency, size and form of JVs by industry in which

they were established.

Table 3 ranks all industries, defined by SDC original industry classification, according to

the number of JV deals between 1990 and 2000. We find more than half of all JV deals clustered

in only ten industries, with the largest number of JV deals in business services7 (13.6% of all JV

deals), followed by the prepackaged software industry (8.2%). The remaining top-tenindustries are: wholesale trade of durable and non-durable goods (6.7% and 2.9%, respectively),

drugs (5.3%), electronic and electrical equipment (4.6%), investment and commodity firms

(3.9%)8, chemicals and allied products (3.4%), telecommunications (3.0%), and communications

equipment (2.9%).

With the exception of the wholesale trade of durable and non-durable goods, business

services, and investment firms, the top-ten industries are technologically intensive. These are

typically riskier industries, so that JVs often become the preferred form of organizational

cooperation because they allow the partners greater ability to reduce risk. Compared with arms-

length contracting, for example, the risk is lower in JVs because partners share the costs,

technologies and know-how, reducing uncertainties related to development and employment of

the risky project. On the other hand, compared with M&As, risk is lower in JVs because they do

7 SDC defines the business services industry very broadly. The SIC codes used by SDC are: 7322-Adjustment and collection services; 7323-Credit reporting services; 7331-Direct mail advertising services;


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not require permanent transfer of assets and control (i.e., the parents respective companies stay

intact), and, furthermore, if the project proves unsuccessful, the parents can quickly and

inexpensively dissolve the JV.

The results are confirmed for JVs with cross-border participants, multi-regional JVs and

domestic JVs. The frequency rankings within each of the three sub-groups are similar to that of

the full sample. The only substantial difference is found in the top two industries among

domestic JVs (business services and prepackaged software), which exhibit a somewhat greater

concentration of deals compared to the full sample. Together, these two industries accounted for30.5% of all domestic JV deals, which is more than in the full sample (21.8%), in the sub-group

of JVs with cross-border participants (15.8%), and among multi-regional JVs (15.7%). It is

possible that this concentration is related to country clustering. We revisit this issue later in the

paper in our discussion of the distribution of JVs by country in which they are established.

Table 4 reports mean and median capitalization and cost of JVs by industry. In the full

sample, the industries with the highest mean estimated capitalization are aerospace and aircraft

(466.6 million US dollars), oil and gas (359.5 million US dollars), and telecommunications

(202.3 million US dollars). The same result holds for mean estimated cost, with the exception

that the telecommunications industry (399.2 million US dollars) is replaced by the paper and

allied products industry (729.9 million US dollars). Within the top-ten, telecommunications

has the highest mean estimated capitalization (202.3 million US dollars), followed by the

communications equipment (124.3 million US dollars) and the chemicals and allied products

industries (76.2 million US dollars). Similar results hold for estimated cost, with the business

i i d t ti th d hi h t (237 5 illi US d ll )


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institutions industry has the largest mean estimated cost (907.3 million US dollars) and the

electric, gas and water distribution industry has the third largest mean estimated cost (599.5

million US dollars) for domestic JVs. Although these results are somewhat interesting, we do not

have sufficient information regarding the dollar size of JVs to draw meaningful conclusions from

our observations.

Table 5 presents evidence on the relationship between the two forms of JVs (strategic

alliances versus independent JV firms) and the industries in which they occur. The business

services, prepackaged software, and wholesale trade of durable goods industries accounted for themost strategic alliances, with 17.8%, 13.0% and 9.0% of all deals, respectively. Among

independent JV firms, the industries with the highest concentration of deals were business

services, chemical and allied products, and transportation equipment (8.1%, 5.5% and 4.7%,

respectively).

Noteworthy differences in the industry distribution of strategic alliances and independent

JV firms are revealed in Table 5. For example, the prepackaged software industry accounted for

13% of all strategic alliances but only 2.0% of all independent JV firms. Similarly, the drug

industry experienced 7.9% of all strategic alliances but only 1.8% of all independent JV firms.

These substantial differences suggest that strategic alliances and independent JV firms serve

inherently different purposes in certain industries. It is important that we improve our

understanding of the factors that influence companies in certain industries to prefer strategic

alliances over independent JV firms, and thus more research is needed in this area.

We also investigate the forms of JVs that are the most frequent in each industry 9. We

fi d th t t t i lli t f t i th k d ft i d t h 89 5%


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different countries. Examples of these assets are technologies, management practices, accounting

procedures and governance standards.

Overall, 50.4% of strategic alliances have cross-border participants, with the highest

percentage of strategic alliances with cross-border participants in the air transportation and

shipping industry. Of 271 transactions in that industry, 229 (84.5%) had cross-border

participants. The two industries with the highest concentration of JV transactions (i.e., business

services and prepackaged software) were among the industries with the lowest ratios of strategic

alliances with cross-border participants. Of 6,077 and 4,435 strategic alliances in the businessservices and prepackaged software industries, respectively, only 2,443 (40.2%) and 1,552 (35%)

transactions had cross-border participants.

The frequency of transactions with cross-border participants in independent JV firms is

higher than it is for strategic alliances. For the average industry, 71.1% of independent JV firms

were established by cross-border participants, as compared with only 50.4% of strategic alliances.

Of 42 independent JV deals in the tobacco products industry, 41 (97.6%) transactions had cross-

border participants, the highest ratio for this sub-group. Similarly for strategic alliances, the

business services and prepackaged software industries account for some of the lowest frequencies

of deals with cross-border participants (40.2% and 35.0%, respectively).

An important observation derived from Table 5 is the correlation of 0.694 between the

percentage of deals with cross-border participants in strategic alliances and in independent JV

firms. This moderately high correlation is indicative of a tendency for industries to have a

substantial percentage of deals with cross-border participants in both strategic alliances and

i d d t JV fi O th th h d th l i d t i i hi h t t i lli


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and services. While the distribution of heterogeneous JVs by industry is similar to that of the full

sample 10, the findings regarding the within-industry frequency of heterogeneous JVs are quite

interesting.

Our results indicate that, for the average industry, 80.1% of JVs are heterogeneous,

pointing to substantial intra-industry cooperation in JVs. For most industries in the top-ten list,

the percentage of heterogeneous JVs is high, with the greatest frequency (98.0%) in the wholesale

trade of durable goods industry. While similar results are observed for many industries outside

the top-ten list, a few industries have relatively low ratios of heterogeneous JVs. The threeindustries with the lowest frequency are mining, legal services, and air transportation and

shipping, with heterogeneous JVs accounting for 40.4%, 45.2% and 47.2%, respectively, of all

JVs. Surprisingly, for the drug industry, which is on the top-ten list, only 64.3% of JVs are

heterogeneous, which is less than the percentage for many other industries on this list.

We do not have a good explanation as to why the frequency of heterogeneous JVs is low

in some industries. Clearly, because the operations of the mining and legal services industries are

unique, firms in these industries exhibit little cooperation with firms from other industries.

However, it is not clear why only 64.3% of drug industry JVs are heterogeneous, especially in

light of the fact that that this is a broad, consumer-oriented, research-intensive industry.

We also attempt to understand the frequency of the forms of JVs (strategic alliances

versus independent JV firms) among heterogeneous transactions. After sub-dividing

heterogeneous JVs into the two forms 11, we find a 59.5% correlation between the frequency of

heterogeneous JVs and the usage of strategic alliances. This result implies that, when partners

f diff t i d t i t th lik l t d i t t i lli It i


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According to the SDC, licensing-agreement JVs arise when one partner grants an

exclusive, simple or cross licensing agreement to another partner. Technology-agreement JVs

are created when an existing or new technology is transferred from one partner to another.

Exploration-agreement JVs arise in order to explore natural resources, such as oil, gas or

minerals. Manufacturing, marketing, and R&D-agreement JVs are deals which are based on

some kind of manufacturing, marketing or R&D agreement among the partners. Supply-

agreement JVs are deals in which one or more participants supply materials to other participants

who then use the materials to create finished products. Lastly, equipment-manufacturing/value-

added reseller-agreement JVs are deals where the original manufacturer supplies a product to

create and add value to a final product, usually computer equipment or software.

Panel A of Table 6 reports the frequency of the different types of JVs in the dataset.

Marketing-agreement JVs are most frequent (28.4% of all deals), followed by manufacturing-

(22.8%), technology- (18.6%), R&D- (16.7%) and licensing-agreement JVs (15.5%). The three

most infrequent types are exploration, supply and equipment manufacturing agreements, with

only 3.1%, 2.8% and 1.5% of all deals, respectively. We note that these frequencies are inflated

(i.e., sum to more than 100%) because any given JV can belong to more than one type.

In order to better understand which JVs can be of multiple types, we report the

correlation matrix for the different types of JVs (Panel B of Table 6) and make several

observations. First, the data indicate that, when firms collaborate in the areas of technology,

R&D, manufacturing or marketing, they often use licenses (48.7% of licensing-agreement JVs are

also technology agreements, 33.3% are marketing agreements, 21.2% are R&D agreements, and

19 6% f t i t ) S d t h l t JV ft d i


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highest mean for both estimated capitalization and cost (220 and 709.3 million US dollars,

respectively), primarily because of a number of very large exploration deals established by

multinational energy companies and host governments. Marketing-agreement JVs have the

lowest mean estimated capitalization (24.7 million US dollars), and are among those with the

lowest mean estimated cost (94.1 million of US dollars), probably because they require the least

commitment of real assets. The size of manufacturing-agreement JVs, whose mean estimated

capitalization and cost are 57.7 and 165.5 million US dollars, respectively, is probably the most

meaningful in the dataset because these are based on the largest number of observations. Lastly,

technology-agreement JVs and R&D-agreement JVs are similar in size. This is likely a

consequence of the fact that they are somewhat highly correlated since they represent similar

fundamental activities.

Next, we provide evidence on the relationship between the type of JV and the industry in

which they occur. Table 7 shows the distribution of JVs by type and industry, and documents the

existence of industry clustering. In addition, we report the amount of cross-border activity as

related to type-industry dynamics.

Of the eight types of JVs, exploration agreements exhibit the highest degree of industry

clustering, as one would expect. Two industries, oil and gas together with mining, account for

95.1% of all exploration-agreement JVs. This high degree of industry clustering is not surprising,

given the unique nature of natural resource exploration. Of 804 exploration-agreement JVs in the

oil and gas industry and 969 in the mining industry, 73.3% and 57.2% of transactions,

respectively, had cross-border participants. The higher than average (56.7%) ratio of transactions

ith b d ti i t i th il d i d t ibl b tt ib t d t it t d d


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cross-border participants within licensing-agreement JVs is similar to that within marketing-

agreement JVs (53.5% versus 60.9%).

Lastly, the industry distribution of supply-agreement JVs closely resembles that of

equipment manufacturing-agreement JVs; the correlation coefficient is 0.912. Both types of

agreements are heavily concentrated in the wholesale trade of durable goods industry (18.1% and

30.1% of all supply and equipment manufacturing agreements, respectively) and the prepackaged

software industry (10.3% and 18.3%, respectively). Outside the top-ten industries, computer

and office equipment accounted for 7.8% of all supply agreements and 11.2% of all equipment

manufacturing agreements.

Our results document that equipment manufacturing-agreement JVs are heavily

concentrated in the wholesale trade of durable goods industry (30.1% of all deals). According to

the SDC, these JVs are transactions in which the original manufacturer supplies a product to

create and add value to a final product, and they should be common in the computer equipment

and software industries. While our results confirm this observation, we also document the fact

that equipment manufacturing-agreement JVs are frequent in the trade of durable goods industry.

This finding may have significance for researchers studying the intricate relationships among

participants in supplier-manufacturer-customer chains.

Distribution of JVs by Country

In this section, we describe the geographic distribution of JVs. Table 8 presents evidence

on the distribution of JVs by form and country of operations. Table 9 describes the distribution

b d t f ti T bl 8 d t th i t f b t ti l t


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67.1% of domestic JVs. The latter experienced 10.5% of JVs with cross-border participants and

only 1.8% of domestic JVs. These noteworthy differences can be attributed to differences in the

economic development of the two nations.

The United States plays a dominant role in the global distribution of domestic JVs

because of its active domestic cooperative market. The enormous size of its capital markets

combined with stable political and legal environments make it relatively easy for domestic firms

to cooperate. Consequently, 67.1% of domestic JVs occurred in the United States.

On the other hand, relative to other countries, the United States generates a much smaller

number of JVs with cross-border participants. While it still has a leading position (20.9% of all

JVs with cross-border participants were established in the United States), other countries, such as

China and Japan, have narrowed the gap, generating 10.5% and 7.8% of all JVs with cross-border

participants, respectively. This result might be informative to researchers analyzing the behavior

of MNCs who seek to better understand the factors affecting economic globalization.

Additional results in Table 8 indicate that strategic alliances have much stronger country

clustering than do independent JV firms. The top-seven countries generated 72.9% of strategic

alliances and 51.1% of independent JV firms. The United States alone accounted for more than

half of all strategic alliances (52.8%), followed by Japan (7.8%) and Canada (3.5%). The United

States accounted for only 18.7% of independent JV firms, followed by China (13.7%) and Japan

(5.1%). Some countries outside the top-seven accounted for a relatively large number of

independent JV firms, including India (3.6%) and Malaysia (3.3%).

The difference between the United States and China in terms of the frequency of strategic

lli d i d d t JV i b tt ib t d t diff i i d l t


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Table 9 reports the distribution of various types of JVs by country of operations.

Analysis of this distribution can improve our understanding of host countries specializations

regarding these types of activities. Two primary conclusions are apparent from an examination of

Table 9. First, the United States is the leader in almost all types of JVs16, which is not surprising

given the size of the U.S. economy. Second, JVs with cross-border participants are less frequent

in the United States than in other countries. This result is pr imarily driven by the high level of

domestic cooperative activity in the United States. Consequently, the frequency of JVs with

cross-border participants is lower in the United States.

Our observations of each type of JV reveal that the United States generated 62.3% of all

licensing agreements, followed by Japan (6.2%), Canada (3.3%) and the United Kingdom (2.7%).

Only 32.2% of licensing-agreement JVs established in the United States had cross-border

participants. In Japan, Canada and the United Kingdom, licensing-agreement JVs had much

higher ratios of cross-border participants (93.3%, 71.1% and 76.3%, respectively).

Technology- and R&D-agreement JVs exhibit similar country clustering. The United

States generated the majority of these transactions (57.9% and 58.1%, respectively), followed by

Japan (8.3% and 8.5%, respectively), China (3.9% and 1.9%, respectively) and the United

Kingdom (2.7% and 2.7%, respectively). China accounted for a somewhat greater number of

technology-agreement JVs (3.9%) than R&D-agreement JVs (1.9%), probably because the former

are more production oriented than the latter.

The only category for which the United States is not the leading country is exploration-

agreement JVs. Australia generated the largest share (14.8% of all transactions), followed by the

U it d St t (14 4%) C d (13 2%) d th R i F d ti (4 1%) Th ti i ti f


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On the other hand, the substantial number of these agreements in China and India adds to the

growing evidence on outsourcing of production from expensive- to cheap-labor countries. The

degree of foreign participation in manufacturing-agreement JVs is quite high. In the United

States, 44.0% of manufacturing-agreement JVs had cross-border participants, the highest ratio for

any type of JV in the U.S. In China and India, almost all manufacturing-agreement JVs had

cross-border participants (92.4% and 90.7% of the transactions, respectively), which is solely a

consequence of the outsourcing phenomenon. In Japan, 71.3% of manufacturing-agreement JVs

had cross-border participants, indicating that, while foreigners play a substantial role in Japanese

manufacturing-agreement JVs, some domestic firms there continue to cooperate with each other

for production reasons.

Further investigation of this issue reveals that 50.4% 17 of 240 Japanese manufacturing-

agreement JVs that did not have cross-border participants (i.e., 28.7% of 835 manufacturing-

agreement JVs) were established in technologically advanced industries. That is, 53 (22.1% of

240) transactions were established in the chemicals and allied products industry, 45 (18.8%) in

the electronic and electrical equipment industry and 23 (9.6%) in the transportation equipment

industry. We see that domestic Japanese manufacturing-agreement JVs cluster in high-tech

industries, possibly as a consequence of these firms unwillingness to share technology with

foreigners, which is partially an artifact of the Keiretsu system. This result might have

importance for researchers who study industrial organization of the Japanese economy.

Marketing-, supply- and equipment manufacturing-agreement JVs cluster in the United

States, Japan and China, but otherwise, the frequency of transactions is fairly uniform. An

i t t b ti i th it f i t f t i t JV t bli h d i


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confirmed for JVs with cross-border participants, multi-regional JVs and domestic JVs.

Examination of these data reveals that partners of lower count have lower equity stake in the JV;

that is, on average, the second partner has less equity ownership than the first, the third partner

has less ownership than the second and so on. The SDC does not assign any meaning to the order

in which partners in the JV are listed18, so these results are apparently related to the fact that the

media list the partners in order of relative importance within the JV. This observation might be

important to researchers who seek to understand the acquirer-target dynamics in JVs.

The most important finding from Table 10 is the strong preference for equal ownership

among JV partners. The empirical evidence shows that, in 71.0% of two-partner JVs, the owners

have equal stakes (i.e., both have 50% ownership). Given that two-partner JVs represent 87.02%

of global JV activity (see Panel B of Table 1), it is clear that that equal ownership is the dominant

form of control. For three-, four- and five-partner JVs, the frequency of transactions with equal

stakes is also relatively high (36.1%, 40.9% and 37.8% of all transactions, respectively), but

significantly less than for two-partner JVs. There may be two reasons for these results. First, as

the number of partners increases beyond two, it becomes increasingly difficult for partners to

agree on equal stakes. Second, in deals with numerous partners, it becomes increasingly unlikely

that each partner contributes equal assets to the JV. Consequently, it is reasonable to find that, as

the number of participant in the JV increases, the probability that they have equal stakes

decreases. We confirm these findings by looking separately at JVs with cross-border participants,

multi-regional JVs and domestic JVs.

Similar results have been previously reported by Hauswald and Hege (2004), who used

th SDC d t t l t t A i JV Th l d th t l hi i


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industry and country clustering, and the partners in these deals have a clear preference for equal

ownership.

While the theoretical research continues to develop a better understanding of the structure

of various organizational forms, more work is needed in addressing the dynamic relationship

among these forms. In particular, under what conditions do firms choose one form of cooperation

and then extend it to a more complex form, or sometimes extend to a simple form. For example,

when do JVs and alliances lead to M&As and takeovers, and vise versa? When do firms start with

arms-length contracts, then continue to JVs and alliances, and then to M&As and takeovers?

These questions are very important and, if answered, could improve on our understanding of the

factors that affect the evolution of firms organizational structure.


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Panel A -Frequency of Joint Ventures (JVs)

N (%)

All JVs 60446 100%with disclosed Estimated Capitalization 4484 7.42%

with disclosed Estimated Cost 4487 7.42%with disclosed both Estimated Capitalization and Cost 402 0.67%

JVs w/ Cross-Border Participants 35495 58.72%

Multi-regional JVs 5839 9.66%

JVs w/ Cross-Border Participants & Multi-regional 5626 9.31%

Domestic JVs 22658 37.48%

Panel B - Number of Participants in JVs

participants: N % N % N % N %

2 52597 87.02% 29626 83.47% 5152 88.23% 20793 91.77%

3 5484 9.07% 4071 11.47% 469 8.03% 1325 5.85%

4 1406 2.33% 1069 3.01% 123 2.11% 319 1.41%

5 529 0.88% 417 1.17% 56 0.96% 108 0.48%

>5 (max=20) 426 0.70% 312 0.88% 39 0.67% 113 0.50%

Total 60442 100.00% 35495 100.00% 5839 100.00% 22658 100.00%

Panel C - Number of Countries where JVs will Operate

countries: N % N % N % N %

1 51400 85.0% 28578 80.5% _- _-_ 22642 99.93%

2 4930 8.2% 4508 12.7% 5295 90.68% 11 0.05%

3 356 0.6% 319 0.9% 332 5.69% 2 0.01%

4 103 0.2% 92 0.3% 99 1.70% 3 0.01%

>4 (max=18) 115 0.2% 100 0.3% 113 1.94% 0 0.00%

Missing Country 3538 5.9% 1898 5.3% 0 0.00% 0 0.00%

Total 60442 100.00% 35495 100.00% 5839 100.00% 22658 100.00%

Panel D -Form of JVs

Form N % N % N % N %

All JVs JVs w/ Cross-Border Multi-regional JVs Domestic JVs

Table 1Summary Statistics for Joint Ventures




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All JVs JVs w/ Cross-Border Participants

Est. Capitalization Estimated Cost Est. Capitalization Estimated Cost

Year N Mean Median N obs Mean Median N obs N Mean Median N obs Mean Median N obs

1990 3034 228.1 20.0 210 269.1 41.3 67 2012 263.8 17.3 163 296.1 42.0 53

1991 5193 91.1 8.8 529 181.7 34.5 236 3367 87.1 8.4 442 220.1 48.5 1771992 5208 75.8 9.0 338 222.8 33.6 225 2945 82.3 8.9 278 215.9 52.8 167

1993 6139 90.1 10.0 711 295.4 27.7 443 3816 75.5 10.0 582 336.4 30.0 346

1994 7527 41.8 6.0 792 236.2 22.0 1005 4758 45.3 7.1 667 224.6 22.0 774

1995 8044 40.9 6.6 636 233.6 30.0 1101 5070 42.8 6.5 529 232.7 30.0 854

1996 4296 70.0 7.7 252 246.1 30.0 397 2608 79.2 7.8 214 253.1 30.0 287

1997 5540 106.5 10.0 385 304.5 50.0 363 3076 117.9 10.0 309 370.9 57.8 255

1998 4910 96.4 13.2 229 556.9 49.2 244 2635 111.5 20.0 157 690.2 54.6 176

1999 5043 86.6 5.0 160 306.4 51.3 224 2486 76.7 6.5 108 270.0 50.0 119

2000 5512 61.9 3.2 242 207.5 30.7 182 2722 100.1 4.7 111 225.0 46.8 119

Total 60446 79.1 8.0 4484 264.6 30.0 4487 35495 81.9 8.6 3560 278.7 30.0 3327

Multi-Regional JVs Domestic JVs

Est. Capitalization Estimated Cost Est. Capitalization Estimated Cost

Year N Mean Median N obs Mean Median N obs N Mean Median N obs Mean Median N obs

1990 121 198.6 30.0 6 340.4 269.3 4 411 106.3 28.3 44 275.3 45.2 8

1991 260 161.1 9.1 20 382.0 200.0 15 821 117.3 15.2 81 111.4 47.6 31

1992 1244 47.7 4.5 99 264.4 100.0 48 2132 50.0 10.0 54 246.8 11.3 56

1993 869 73.8 6.5 87 813.0 37.0 35 2186 167.9 10.0 118 151.8 10.1 92

1994 843 47.2 5.2 26 333.3 50.0 51 2700 23.6 3.0 125 281.7 25.5 2251995 662 62.3 4.3 23 432.3 63.5 48 2901 32.4 6.8 105 239.4 32.0 241

1996 279 52.0 23.7 12 126.1 23.5 21 1629 18.0 7.7 38 231.4 33.0 107

1997 503 153.1 16.5 64 698.3 50.5 38 2378 57.3 4.1 68 148.6 30.9 100

1998 492 108.0 26.8 46 572.1 283.5 24 2215 65.8 7.0 69 212.0 25.2 68

1999 325 17.5 17.5 2 566.0 47.5 4 2530 109.2 3.3 51 347.7 52.5 105

2000 241 180.1 3.3 3 235.3 107.6 4 2755 29.2 2.0 129 174.5 21.0 63

Total 5839 88.1 9.8 388 452.4 57.5 292 22658 69.7 5.6 882 233.6 28.5 1096

Table 2Frequency and Size of Joint Ventures by Year

Graph 1

Yearly Frequency of JV Deals

8000

9000

All JVs


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Industry of JV N % Cum % N % Cum % N % Cum % N % Cum %

Business Services 8205 13.6% 13.6% 3740 10.5% 10.5% 564 9.7% 9.7% 4308 19.0% 19.0%

Prepackaged Software 4953 8.2% 21.8% 1852 5.2% 15.8% 353 6.0% 15.7% 2608 11.5% 30.5%

Wholesale Trade-Durable Goods 4026 6.7% 28.4% 2259 6.4% 22.1% 485 8.3% 24.0% 1566 6.9% 37.4%Drugs 3201 5.3% 33.7% 1824 5.1% 27.3% 491 8.4% 32.4% 1155 5.1% 42.5%

Electronic and Electrical Equipment 2785 4.6% 38.3% 1859 5.2% 32.5% 399 6.8% 39.3% 805 3.6% 46.1%

Investment & Commodity Firms/Dealers/Exch. 2375 3.9% 42.3% 1362 3.8% 36.3% 156 2.7% 41.9% 989 4.4% 50.5%

Chemicals and Allied Products 2050 3.4% 45.7% 1571 4.4% 40.8% 251 4.3% 46.2% 437 1.9% 52.4%

Telecommunications 1811 3.0% 48.6% 1129 3.2% 43.9% 185 3.2% 49.4% 632 2.8% 55.2%

Communications Equipment 1783 2.9% 51.6% 1059 3.0% 46.9% 233 4.0% 53.4% 590 2.6% 57.8%

Wholesale Trade-Nondurable Goods 1748 2.9% 54.5% 1142 3.2% 50.1% 228 3.9% 57.3% 568 2.5% 60.3%

Oil and Gas; Petroleum Refining 1586 2.6% 1142 3.2% 126 2.2% 427 1.9%

Transportation Equipment 1579 2.6% 1287 3.6% 174 3.0% 275 1.2%

Computer and Office Equipment 1484 2.5% 788 2.2% 168 2.9% 519 2.3%Measuring, Medical, Photo Equipment; Clocks 1340 2.2% 728 2.1% 177 3.0% 525 2.3%

Mining 1318 2.2% 774 2.2% 43 0.7% 540 2.4%

Machinery 1258 2.1% 962 2.7% 148 2.5% 267 1.2%

Real Estate; Mortgage Bankers and Brokers 1224 2.0% 656 1.8% 39 0.7% 559 2.5%

Metal and Metal Products 1181 2.0% 923 2.6% 117 2.0% 234 1.0%

Construction Firms 1126 1.9% 785 2.2% 83 1.4% 330 1.5%

Food and Kindred Products 1071 1.8% 844 2.4% 85 1.5% 218 1.0%

Transportation and Shipping (except air) 1062 1.8% 753 2.1% 164 2.8% 286 1.3%

Electric, Gas, and Water Distribution 978 1.6% 624 1.8% 71 1.2% 354 1.6%

Radio and Television Broadcasting Stations 798 1.3% 434 1.2% 66 1.1% 349 1.5%Insurance 765 1.3% 417 1.2% 45 0.8% 343 1.5%

Motion Picture Production and Distribution 575 1.0% 300 0.8% 48 0.8% 259 1.1%

Air Transportation and Shipping 523 0.9% 437 1.2% 150 2.6% 83 0.4%

Textile and Apparel Products 469 0.8% 308 0.9% 44 0.8% 153 0.7%

Stone, Clay, Glass, and Concrete Products 462 0.8% 368 1.0% 37 0.6% 84 0.4%

Miscellaneous Retail Trade 441 0.7% 237 0.7% 24 0.4% 195 0.9%

Printing, Publishing, and Allied Services 441 0.7% 240 0.7% 26 0.4% 190 0.8%

Credit Institutions 423 0.7% 227 0.6% 35 0.6% 191 0.8%

Rubber and Miscellaneous Plastic Products 417 0.7% 321 0.9% 40 0.7% 86 0.4%

Commercial Banks, Bank Holding Companies 397 0.7% 282 0.8% 40 0.7% 112 0.5%Health Services 393 0.7% 105 0.3% 17 0.3% 286 1.3%

Hotels and Casinos 381 0.6% 258 0.7% 23 0.4% 117 0.5%

Amusement and Recreation Services 341 0.6% 174 0.5% 18 0.3% 161 0.7%

A d Ai ft 332 0 5% 257 0 7% 75 1 3% 67 0 3%

Table 3

All JVsJVs w/ Cross-Border

ParticipantsMulti-Regional JVs Domestic JVs

Frequency of Joint Ventures by Industry


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JVs w/ Cross-Border Participants Multi-Regional JVs Domestic JVs

(Data are in US$ Mil)

Industry of JV Mean Median N obs Mean Median N obs Mean Median N obs Mean Median N obs Mean Median N obs Mean Median N obs Mean Median N obs Mean Median N obs

Business Services 41.9 2.4 275 237.5 24.4 232 41.0 2.1 176 268.1 26.1 135 98.0 4.0 13 1354.1 47.8 17 43.6 2.8 99 197.6 18.0 95

Prepackaged Software 14.6 2.0 69 61.2 7.0 68 16.3 1.8 47 27.8 5.3 30 10.2 1.0 7 34.4 34.4 2 10.5 2.2 21 102.7 11.0 32

Wholesale Trade-Durable Goods 13.1 1.5 188 192.5 11.0 80 12.4 1.5 153 183.9 8.0 48 10.5 0.8 18 64.0 27.8 4 17.2 1.8 33 232.0 24.7 28

Drugs 47.9 10.0 85 28.3 15.8 165 51.9 10.0 63 29.3 17.1 112 307.6 8.4 10 44.6 30.0 25 9.4 5.8 20 27.7 20.0 49

Electronic and Electrical Equipment 59.4 9.0 279 211.7 25.0 237 68.6 9.0 231 174.0 26.9 194 81.5 13.8 22 247.8 63.5 14 15.6 8.2 46 410.6 16.8 40

Investment & Commodity Firms/Dealers/Exc 54.8 10.1 141 114.4 42.5 69 48.7 10.1 112 106.4 31.3 42 57.4 22.9 16 294.0 200.0 6 78.2 12.9 29 126.7 45.7 27

Chemicals and Allied Products 76.2 7.9 272 140.1 44.5 310 53.3 8.1 230 143.8 46.4 263 96.1 14.0 31 182.0 118.7 22 216.8 6.2 39 117.6 33.0 43

Telecommunications 202.3 12.5 103 399.2 61.7 140 212.1 12.5 85 418.5 60.0 107 70.8 15.0 13 666.5 508.1 12 166.7 3.5 15 346.1 100.0 32

Communications Equipment 124.3 10.0 111 235.1 20.0 111 102.9 10.0 98 258.2 20.1 90 177.3 18.8 10 256.9 86.4 17 285.1 6.3 13 178.4 45.5 15

Wholesale Trade-Nondurable Goods 62.8 2.5 106 108.4 15.0 67 82.2 2.0 76 124.8 20.2 50 7.6 1.2 9 13.6 13.4 6 13.9 3.0 29 62.7 3.8 16

Oil and Gas; Petroleum Refining 359.5 40.0 126 1075.7 117.0 249 395.6 42.0 100 1148.3 225.0 200 318.8 28.5 9 1895.8 450.0 24 227.9 40.0 25 810.0 44.0 47

Transportation Equipment 80.5 12.0 278 191.1 27.3 218 84.5 12.5 246 205.8 29.2 200 99.1 10.4 33 199.0 67.5 12 61.1 12.1 26 27.4 17.4 18

Computer and Office Equipment 23.5 5.0 68 178.9 15.0 50 17.5 4.8 47 150.7 19.0 31 8.7 3.9 10 38.8 38.8 2 35.6 6.5 19 321.2 10.0 13

Measuring, Medical, Photo Equipment; Clocks 27.8 4.9 58 127.9 5.6 63 30.7 4.8 49 137.4 6.0 43 72.7 10.0 7 18.5 18.5 4 13.1 8.0 8 124.9 3.0 17

Mining 79.4 8.8 104 112.8 8.0 200 103.1 11.1 70 154.1 15.0 120 2.8 2.7 3 305.7 45.0 8 31.6 6.7 33 50.8 3.0 80

Machinery 52.0 6.0 177 56.8 20.0 112 53.0 6.0 148 61.3 20.0 92 113.8 5.3 10 92.4 65.0 10 46.9 6.8 29 36.2 15.6 20

Real Estate; Mortgage Bankers and Brokers 94.2 19.7 164 256.8 63.8 330 93.0 20.4 122 183.8 60.0 203 211.8 31.6 5 86.5 99.1 4 97.7 7.6 42 378.4 76.2 125

Metal and Metal Products 56.0 10.0 231 214.5 30.0 186 56.8 10.8 200 192.9 30.0 154 84.1 6.0 25 410.8 170.2 8 50.3 5.0 27 338.3 35.0 29

Construction Firms 167.4 15.0 118 525.3 87.0 253 179.1 15.0 97 647.2 99.0 181 288.3 38.0 11 463.4 84.3 18 113.1 12.5 21 225.1 78.0 69

Food and Kindred Products 48.5 10.7 163 49.7 16.8 177 52.5 11.9 145 44.5 17.7 154 10.1 6.0 7 12.1 13.5 5 17.3 10.4 17 87.8 10.2 22

Transportation and Shipping (except air) 35.8 3.8 110 190.2 19.5 91 32.5 3.0 93 220.5 19.5 71 16.6 5.1 18 108.5 18.0 7 54.0 14.5 17 82.9 17.5 20

Electric, Gas, and Water Distribution 165.5 36.3 101 610.8 180.0 222 207.9 46.0 66 614.5 200.0 167 90.1 30.0 6 818.0 458.0 13 85.7 29.0 35 599.5 138.0 55

Radio and Television Broadcasting Stations 155.9 30.0 49 204.3 51.7 58 185.7 21.1 28 258.2 122.5 30 75.0 75.0 2 376.3 251.8 4 117.1 30.0 20 146.5 30.0 28

Insurance 105.1 11.4 90 34.5 16.0 15 102.6 10.9 70 25.6 16.0 13 22.2 25.0 3 11.4 11.4 2 114.0 19.4 20 92.2 92.2 2

Motion Picture Production and Distribution 178.6 23.1 26 53.8 30.0 33 218.4 23.1 18 72.4 60.0 20 176.7 60.0 3 86.0 86.0 2 89.3 26.8 8 25.2 9.3 13

Air Transportation and Shipping 62.0 11.0 37 240.9 70.0 25 69.3 11.0 28 258.4 76.0 23 100.0 100.0 1 613.8 475.0 4 39.1 9.4 9 39.7 39.7 2

Textile and Apparel Products 15.5 4.7 96 44.1 15.6 52 16.9 4.6 83 34.4 15.0 42 56.1 5.6 12 27.5 27.5 2 5.5 3.8 10 85.1 35.0 10

Stone, Clay, Glass, and Concrete Products 39.3 11.4 103 95.8 41.3 88 43.1 12.3 88 98.9 43.5 79 66.7 33.3 7 102.3 100.0 7 17.0 9.8 15 83.9 100.0 7

Miscellaneous Retail Trade 25.6 2.2 36 285.7 110.0 17 28.2 1.8 23 361.4 70.0 12 1.4 0.3 3 111.5 111.5 1 22.8 4.2 12 102.0 123.8 4

Printing, Publishing, and Allied Services 76.0 9.6 16 82.5 30.0 13 92.4 12.0 13 115.4 68.0 9 293.5 293.5 2 . . . 4.9 4.7 3 8.5 9.0 4

Credit Institutions 27.0 5.5 45 523.7 100.0 9 23.6 5.0 34 331.9 98.6 6 5.8 5.7 6 . . . 37.7 16.2 11 907.3 100.0 3

Rubber and Miscellaneous Plastic Products 55.4 5.5 67 64.3 20.4 59 63.5 6.0 57 67.0 21.1 50 486.0 486.0 2 85.4 70.2 4 9.2 3.0 10 41.1 17.4 8

Commercial Banks, Bank Holding Companies 37.0 16.2 83 25.8 10.0 11 29.5 15.0 73 25.8 10.0 11 37.3 40.0 6 100.0 100.0 1 91.2 23.2 10 . . .

Health Services 15.4 6.5 20 61.1 23.4 20 21.4 22.5 9 31.4 26.1 11 50.0 50.0 1 0.4 0.4 1 10.6 3.3 11 97.5 20.0 9

Hotels and Casinos 70.2 40.0 43 106.8 43.9 80 55.9 20.0 33 106.7 37.5 60 60.2 46.7 4 100.0 100.0 1 122.3 54.3 9 97.2 70.0 19

Amusement and Recreation Services 64.1 12.1 26 165.0 50.0 35 86.5 12.1 18 108.9 40.0 21 . . . 8.0 8.0 1 13.8 12.0 8 241.4 73.5 13

Aerospace and Aircraft 466.6 45.0 22 698.2 200.0 33 509.3 45.0 20 739.2 148.0 24 3.2 1.0 3 1068.4 412.0 3 77.4 77.4 1 589.1 380.0 9

Miscellaneous Manufacturing 44.4 2.8 12 4.1 1.4 10 48.4 3.5 11 4.5 1.4 9 . . . 8.0 8.0 1 0.7 0.7 1 0.5 0.5 1

Paper and Allied Products 151.9 10.0 52 729.9 48.5 34 186.1 11.0 42 956.3 45.0 23 2.6 2.6 2 . . . 8.6 1.2 9 256.7 77.7 11

Advertising Services 13.4 0.6 22 53.5 5.0 8 16.7 0.4 17 41.2 32.0 4 23.1 4.5 4 . . . 2.2 0.9 5 65.9 3.8 4

Public Administration 22.6 3.0 5 121.1 60.4 6 36.0 15.0 3 156.4 149.1 4 90.0 90.0 1 327.0 327.0 1 2.5 2.5 2 50.4 50.4 2

Agriculture, Forestry, and Fishing 31.7 4.3 33 33.5 10.3 32 34.7 5.0 23 42.6 12.4 23 26.9 3.3 4 . . . 24.8 0.7 10 10.1 3.3 9

Retail Trade-Eating and Drinking Places 144.3 2.0 21 518.3 8.6 12 166.0 2.0 18 609.1 7.6 10 3.3 3.3 2 0.0 0.0 1 14.0 1.9 3 64.8 64.8 2

Sanitary Services 13.3 7.9 8 40.7 11.0 22 0.2 0.2 2 57.9 12.5 14 . . . 2.0 2.0 2 17.7 16.3 6 12.1 6.0 7

34

All JVs

Table 4Size of Joint Ventures by Industry

Estimated Capitalization Estimated Cost Estimated CostEstimated Capital ization Estimated Cost Estimated Capital ization Estimated Cost Estimated Capital ization


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Soaps, Cosmetics and Personal-Care Products 9.8 7.4 29 24.6 15.1 28 10.0 7.4 23 23.1 15.6 24 13.5 13.5 2 52.8 52.8 2 9.0 6.7 6 9.3 12.0 3

Wood Products, Furniture, and Fixtures 26.6 3.0 37 43.6 25.0 21 31.3 3.0 31 51.5 25.0 15 63.3 2.0 5 . . . 3.2 3.5 5 23.8 15.8 6

Retail Trade-Home Furnishings 12.1 2.9 5 15.4 15.4 1 18.9 6.0 3 15.4 15.4 1 6.0 6.0 1 . . . 1.8 1.8 2 . . .

Retail Trade-General Merchandise & Apparel 41.4 5.5 16 55.3 26.3 12 44.1 6.0 15 32.5 18.7 8 5.0 5.0 1 259.0 259.0 1 1.2 1.2 1 48.2 31.5 3

Educational Services 2.0 0.7 5 31.6 3.6 5 0.4 0.4 1 2.2 2.0 3 . . . 2.0 2.0 1 2.5 0.8 4 75.6 75.6 2

Repair Services 3.3 1.2 18 116.2 1.7 7 2.6 1.1 14 135.3 2.7 6 6.2 6.2 1 1.0 1.0 1 5.5 5.6 4 1.7 1.7 1

Retail Trade-Food Stores 7.9 3.4 14 85.4 19.0 11 7.9 3.4 14 98.6 19.0 9 21.4 21.4 2 500.0 500.0 1 . . . 25.9 25.9 2

Other Financial 9.8 9.6 4 . . . 9.8 9.6 4 . . . 11.3 11.3 2 . . . . . . . . .

Leather and Leather Products 34.4 8.0 8 36.0 10.0 8 34.4 8.0 8 36.0 10.0 8 0.3 0.3 1 . . . . . . . . .

Miscellaneous Services 12.3 4.4 7 1.5 1.5 1 11.9 4.2 6 1.5 1.5 1 . . . . . . 15.2 15.2 1 . . .

Tobacco Products 37.4 35.0 7 89.6 52.5 12 37.4 35.0 7 89.6 52.5 12 48.7 47.5 4 200.0 200.0 1 . . . . . .Holding Companies, Except Banks 48.1 4.0 7 9.0 1.5 3 67.2 76.0 5 13.3 13.3 2 100.0 100.0 1 . . . 0.1 0.1 2 0.4 0.4 1

Social Services 4.5 4.5 1 10.0 10.0 1 . . . . . . . . . . . . 4.5 4.5 1 10.0 10.0 1

Legal Services 0.3 0.3 1 . . . 0.3 0.3 1 . . . 0.3 0.3 1 . . . . . . . . .

Personal Services 3.4 0.8 3 12.0 12.0 2 4.8 4.8 2 . . . . . . . . . 0.8 0.8 1 12.0 12.0 2

Savings and Loans, Mutual Savings Banks 70.0 70.0 2 . . . . . . . . . . . . . . . 70.0 70.0 2 . . .

No Industry Classification & Non-classifiable 158.0 7.4 81 251.4 30.0 73 114.0 6 61 284.2 31 53 144.3 10.8 6 133.3 39 7 340.0 10 17 175.2 32.3 16

35


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Industry of JV N % N% of

all

% within

industry

% JVs w/

cross-

border

partic.

N% of

all

% within

industry

% JVs w/

cross-

border

partic.

N% of

all

% within

industry

Strategic

Alliances (%

within

industry)

Independent

JV firms (%

within

industry)column (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) (m) (n) (o)

Business Services 8205 13.6% 6077 17.8% 74.1% 40.2% 2128 8.1% 25.9% 60.9% 7211 14.7% 87.9% 64.9% 23.0%

Prepackaged Software 4953 8.2% 4435 13.0% 89.5% 35.0% 516 2.0% 10.4% 57.4% 4312 8.8% 87.1% 77.5% 9.5%

Wholesale Trade-Durable Goods 4026 6.7% 3082 9.0% 76.6% 51.3% 944 3.6% 23.4% 71.9% 3945 8.1% 98.0% 75.5% 22.5%

Drugs 3201 5.3% 2714 7.9% 84.8% 54.1% 486 1.8% 15.2% 73.5% 2057 4.2% 64.3% 54.3% 10.0%

Electronic and Electrical Equipment 2785 4.6% 1643 4.8% 59.0% 57.0% 1142 4.3% 41.0% 80.7% 2186 4.5% 78.5% 46.5% 32.0%

Investment & Commodity Firms/Dealers/Exch. 2375 3.9% 1592 4.7% 67.0% 51.5% 783 3.0% 33.0% 69.2% 2040 4.2% 85.9% 62.5% 23.4%

Chemicals and Allied Products 2050 3.4% 615 1.8% 30.0% 64.9% 1435 5.5% 70.0% 81.7% 1539 3.1% 75.1% 23.4% 51.7%

Telecommunications 1811 3.0% 989 2.9% 54.6% 51.5% 822 3.1% 45.4% 75.4% 1374 2.8% 75.9% 41.4% 34.5%

Communications Equipment 1783 2.9% 1180 3.5% 66.2% 47.0% 601 2.3% 33.7% 83.9% 1637 3.3% 91.8% 61.2% 30.5%Wholesale Trade-Nondurable Goods 1748 2.9% 1123 3.3% 64.2% 59.7% 624 2.4% 35.7% 75.6% 1704 3.5% 97.5% 63.4% 34.0%

Oil and Gas; Petroleum Refining 1586 2.6% 406 1.2% 25.6% 61.8% 1179 4.5% 74.3% 75.6% 874 1.8% 55.1% 11.9% 43.2%

Transportation Equipment 1579 2.6% 336 1.0% 21.3% 69.9% 1243 4.7% 78.7% 84.6% 1121 2.3% 71.0% 13.3% 57.7%

Computer and Office Equipment 1484 2.5% 1218 3.6% 82.1% 49.0% 266 1.0% 17.9% 71.8% 1297 2.6% 87.4% 71.4% 16.0%

Measuring, Medical, Photo Equipment; Clocks 1340 2.2% 946 2.8% 70.6% 46.2% 394 1.5% 29.4% 73.9% 1096 2.2% 81.8% 56.8% 25.0%

Mining 1318 2.2% 389 1.1% 29.5% 48.6% 928 3.5% 70.4% 62.9% 532 1.1% 40.4% 9.6% 30.6%

Machinery 1258 2.1% 465 1.4% 37.0% 66.5% 792 3.0% 63.0% 82.4% 1066 2.2% 84.7% 31.9% 52.8%

Real Estate; Mortgage Bankers and Brokers 1224 2.0% 272 0.8% 22.2% 37.1% 952 3.6% 77.8% 58.3% 1017 2.1% 83.1% 18.8% 64.3%

Metal and Metal Products 1181 2.0% 252 0.7% 21.3% 64.7% 929 3.5% 78.7% 81.8% 929 1.9% 78.7% 17.7% 61.0%

Construction Firms 1126 1.9% 290 0.8% 25.8% 63.1% 836 3.2% 74.2% 72.0% 961 2.0% 85.3% 22.5% 62.9%Food and Kindred Products 1071 1.8% 233 0.7% 21.8% 60.1% 838 3.2% 78.2% 84.0% 621 1.3% 58.0% 9.5% 48.5%

Transportation and Shipping (except air) 1062 1.8% 257 0.8% 24.2% 58.0% 805 3.1% 75.8% 75.0% 648 1.3% 61.0% 14.3% 46.7%

Electric, Gas, and Water Distribution 978 1.6% 221 0.6% 22.6% 57.5% 757 2.9% 77.4% 65.7% 768 1.6% 78.5% 16.3% 62.3%

Radio and Television Broadcasting Stations 798 1.3% 331 1.0% 41.5% 47.1% 467 1.8% 58.5% 59.5% 630 1.3% 78.9% 32.5% 46.5%

Insurance 765 1.3% 296 0.9% 38.7% 35.8% 468 1.8% 61.2% 66.2% 483 1.0% 63.1% 23.3% 39.9%

Motion Picture Production and Distribution 575 1.0% 262 0.8% 45.6% 45.8% 313 1.2% 54.4% 57.5% 443 0.9% 77.0% 36.0% 41.0%

Air Transportation and Shipping 523 0.9% 271 0.8% 51.8% 84.5% 252 1.0% 48.2% 82.5% 247 0.5% 47.2% 13.6% 33.7%

Textile and Apparel Products 469 0.8% 177 0.5% 37.7% 37.3% 292 1.1% 62.3% 82.9% 348 0.7% 74.2% 27.1% 47.1%

Stone, Clay, Glass, and Concrete Products 462 0.8% 79 0.2% 17.1% 53.2% 383 1.5% 82.9% 85.1% 363 0.7% 78.6% 14.5% 64.1%

Miscellaneous Retail Trade 441 0.7% 194 0.6% 44.0% 45.4% 247 0.9% 56.0% 60.3% 427 0.9% 96.8% 42.0% 54.9%

Printing, Publishing, and Allied Services 441 0.7% 215 0.6% 48.8% 43.3% 225 0.9% 51.0% 64.9% 266 0.5% 60.3% 32.2% 27.9%

Credit Institutions 423 0.7% 227 0.7% 53.7% 41.9% 195 0.7% 46.1% 67.2% 404 0.8% 95.5% 51.3% 44.0%

Rubber and Miscellaneous Plastic Products 417 0.7% 114 0.3% 27.3% 63.2% 302 1.1% 72.4% 82.1% 368 0.8% 88.2% 25.2% 62.8%

Commercial Banks Bank Holding Companies 397 0 7% 136 0 4% 34 3% 55 9% 261 1 0% 65 7% 78 9% 235 0 5% 59 2% 20 4% 38 8%

Table 5Frequency of Joint Ventures by Form

Heterogeneous JVsAll JVs (Full

sample)Independent JV FirmsStrategic Alliances


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Legal Services 31 0.1% 16 0.0% 51.6% 50.0% 15 0.1% 48.4% 86.7% 14 0.0% 45.2% 16.1% 29.0%

Personal Services 20 0.0% 9 0.0% 45.0% 33.3% 11 0.0% 55.0% 54.5% 19 0.0% 95.0% 45.0% 50.0%

Savings and Loans, Mutual Savings Banks 8 0.0% 5 0.0% 62.5% 40.0% 3 0.0% 37.5% 66.7% 7 0.0% 87.5% 62.5% 25.0%

No Industry Classification & Non-classifiable 1903 3.1% 1309 3.8% 68.8% 52.0% 593 2.3% 31.2% 69.8% 1903 3.9% 100.0% 68.8% 31.1%

Total 60446 100% 34161 100% 26271 100% 48944 100%

Average 50.4% 71.1% 80.1%

Correlation 0.694 0.990 0.595(f)-(j) (m)-(n)(b)-(l)


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Panel A - Frequency of JVs by Type

N (%)

All JVs 60446 100%

Licensing Agreement JVs 9352 15.5%

Technology Agreement JVs 11241 18.6%

Exploration Agreement JVs 1865 3.1%

Manufacturing Agreement JVs 13780 22.8%

Marketing Agreement JVs 17183 28.4%

R&D Agreement JVs 10104 16.7%

Supply Agreement JVs 1721 2.8%

Equipment Manufacturing/Value Added Reseller Agreement JVs 887 1.5%

Panel B - Correlation Across TypesLicensing Technology Exploration Manufacturing Marketing R&D Supply Equipment

Licensing 9352

Technology 4551 (48.7%) 11241

Exploration 18 (0.2%) 24 (0.2%) 1865

Manufacturing 1830 (19.6%) 2706 (24.1%) 47 (2.5%) 13780

Marketing 3118 (33.3%) 3932 (35.0%) 41 (2.2%) 4300 (31.2%) 17183

R&D 1987 (21.2%) 4732 (42.1%) 41 (2.2) 1614 (11.7%) 3533 (20.6%) 10104

Supply 255 (2.7%) 406 (3.6%) 8 (0.4%) 389 (2.8%) 768 (4.5%) 329 (3.3%) 1721

Equipment 146 (1.6%) 329 (2.9%) 4 (0.2%) 146 (1.1%) 564 (3.3%) 140 (1.4%) 491 (28.5%) 887

Panel C - Size of JVs by Type

Mean Median N obs

All JVs

Estimated Capitalization of JV 79.1 8 4484

Estimated Cost of JV 264.6 30 4487

Licensing Agreement JVs

Estimated Capitalization of JV 59.9 5 60Estimated Cost of JV 87.2 10 205

Technology Agreement JVs

Estimated Capitalization of JV 52.1 7.6 400

i d C f 205 0 20 5 3

Table 6Summary Statistics for Frequency and Size of Joint Ventures by Type


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Industry

column (a) (b) (c ) (d) (e) (f) (g) (h) (i) (j) (k) (l) (m) (n) (o) (p)

Business Services 662 7.1% 40.0% 1162 10.3% 46.7% 6 0.3% 66.7% 256 1.9% 55.1% 1839 10.7% 46.2% 1678 16.6% 47.1% 79 4.6% 58.2% 80 9.0% 40.0%

Prepackaged Software 1555 16.6% 35.0% 2082 18.5% 40.6% 2 0.1% 0.0% 264 1.9% 42.8% 1548 9.0% 36.6% 1818 18.0% 35.0% 178 10.3% 30.9% 162 18.3% 25.9%

Wholesale Trade-Durable Goods 475 5.1% 51.8% 618 5.5% 59.5% 3 0.2% 66.7% 228 1.7% 62.3% 3383 19.7% 55.6% 255 2.5% 41.2% 312 18.1% 50.0% 267 30.1% 47.9%Drugs 1423 15.2% 52.1% 1717 15.3% 61.2% . . . 863 6.3% 67.8% 1312 7.6% 65.2% 1765 17.5% 51.6% 110 6.4% 57.3% 13 1.5% 46.2%

Electronic and Electrical Equipment 627 6.7% 56.8% 1037 9.2% 69.8% . . . 1559 11.3% 74.2% 757 4.4% 69.0% 868 8.6% 56.2% 127 7.4% 66.1% 39 4.4% 66.7%

Investment & Commodity Firms/Dealers 1172 12.5% 51.3% 216 1.9% 59.3% 4 0.2% 75.0% 122 0.9% 46.7% 204 1.2% 54.9% 72 0.7% 43.1% 4 0.2% 25.0% 18 2.0% 38.9%

Chemicals and Allied Products 254 2.7% 67.7% 518 4.6% 73.9% 8 0.4% 37.5% 1572 11.4% 79.9% 475 2.8% 74.3% 280 2.8% 55.0% 56 3.3% 73.2% 3 0.3% 100.0%

Telecommunications 129 1.4% 49.6% 431 3.8% 68.7% . . . 70 0.5% 71.4% 275 1.6% 44.7% 151 1.5% 55.6% 44 2.6% 59.1% 15 1.7% 33.3%

Communications Equipment 303 3.2% 42.9% 703 6.3% 62.0% . . . 499 3.6% 77.6% 549 3.2% 57.4% 614 6.1% 48.2% 111 6.4% 56.8% 63 7.1% 49.2%

Wholesale Trade-Nondurable Goods 424 4.5% 54.5% 260 2.3% 68.1% 5 0.3% 40.0% 138 1.0% 65.2% 1423 8.3% 66.1% 104 1.0% 60.6% 59 3.4% 47.5% 2 0.2% 100.0%

Oil and Gas; Petroleum Refining 31 0.3% 77.4% 48 0.4% 66.7% 804 43.1% 73.3% 238 1.7% 82.8% 102 0.6% 72.5% 53 0.5% 49.1% 30 1.7% 66.7% 2 0.2% 100.0%

Transportation Equipment 64 0.7% 75.0% 119 1.1% 78.2% . . . 1343 9.7% 84.1% 309 1.8% 82.5% 158 1.6% 60.8% 40 2.3% 85.0% 8 0.9% 75.0%

Computer and Office Equipment 321 3.4% 46.1% 559 5.0% 60.1% . . . 409 3.0% 68.0% 580 3.4% 54.8% 552 5.5% 44.0% 135 7.8% 56.3% 99 11.2% 57.6%

Measuring, Medical, Photo Equipment; Clocks 343 3.7% 42.3% 453 4.0% 57.0% 1 0.1% 0.0% 540 3.9% 61.9% 499 2.9% 60.3% 469 4.6% 43.5% 64 3.7% 50.0% 22 2.5% 81.8%

Mining 9 0.1% 66.7% 10 0.1% 90.0% 969 52.0% 57.2% 39 0.3% 82.1% 25 0.1% 84.0% 17 0.2% 64.7% 2 0.1% 100.0% 3 0.3% 66.7%

Machinery 128 1.4% 72.7% 218 1.9% 77.1% 9 0.5% 44.4% 860 6.2% 84.1% 331 1.9% 78.9% 225 2.2% 52.9% 53 3.1% 75.5% 13 1.5% 61.5%Real Estate; Mortgage Bankers and Brokers 3 0.0% . 6 0.1% 66.7% 1 0.1% 100.0% 4 0.0% 100.0% 34 0.2% 55.9% 3 0.0% 66.7% 1 0.1% 100.0% 3 0.3% 66.7%

Metal and Metal Products 80 0.9% 63.8% 146 1.3% 78.1% 8 0.4% 75.0% 942 6.8% 80.7% 195 1.1% 74.9% 108 1.1% 55.6% 25 1.5% 92.0% 8 0.9% 87.5%

Construction Firms 10 0.1% 60.0% 21 0.2% 71.4% 6 0.3% 83.3% 75 0.5% 82.7% 29 0.2% 72.4% 14 0.1% 42.9% 15 0.9% 66.7% 3 0.3% 66.7%

Food and Kindred Products 88 0.9% 58.0% 31 0.3% 61.3% 1 0.1% 100.0% 883 6.4% 81.0% 373 2.2% 76.1% 43 0.4% 39.5% 13 0.8% 69.2% 4 0.5% 75.0%

Transportation and Shipping (except air) 9 0.1% 55.6% 9 0.1% 77.8% 3 0.2% 33.3% 12 0.1% 83.3% 71 0.4% 62.0% 5 0.0% 60.0% 12 0.7% 75.0% 4 0.5% 75.0%

Electric, Gas, and Water Distribution 13 0.1% 53.8% 57 0.5% 70.2% 15 0.8% 80.0% 29 0.2% 65.5% 81 0.5% 58.0% 33 0.3% 57.6% 34 2.0% 55.9% 1 0.1% 100.0%

Radio and Television Broadcasting Stations 47 0.5% 53.2% 80 0.7% 47.5% . . . 6 0.0% 33.3% 90 0.5% 43.3% 39 0.4% 33.3% 5 0.3% 80.0% 1 0.1% 100.0%

Insurance 9 0.1% 55.6% 7 0.1% 28.6% . . . 1 0.0% 100.0% 123 0.7% 40.7% 8 0.1% 50.0% 2 0.1% 0.0% 2 0.2% 0.0%

Motion Picture Production and Distribution 67 0.7% 52.2% 17 0.2% 35.3% . . . 23 0.2% 52.2% 152 0.9% 54.6% 23 0.2% 52.2% 2 0.1% 0.0% . . .

Air Transportation and Shipping 2 0.0% 100.0% 10 0.1% 90.0% . . . 7 0.1% 85.7% 94 0.5% 85.1% 6 0.1% 100.0% 3 0.2% 100.0% 1 0.1% 100.0%

Textile and Apparel Products 114 1.2% 28.9% 20 0.2% 50.0% . . . 393 2.9% 70.5% 161 0.9% 60.2% 23 0.2% 47.8% 5 0.3% 40.0% 6 0.7% 66.7%

Stone, Clay, Glass, and Concrete Products 27 0.3% 33.3% 33 0.3% 69.7% 3 0.2% 100.0% 400 2.9% 82.5% 90 0.5% 71.1% 23 0.2% 39.1% 11 0.6% 90.9% 1 0.1% 100.0%

Miscellaneous Retail Trade 28 0.3% 42.9% 11 0.1% 54.5% . . . 17 0.1% 58.8% 224 1.3% 62.5% 3 0.0% 66.7% 9 0.5% 77.8% 1 0.1% 0.0%Printing, Publishing, and Allied Services 46 0.5% 39.1% 13 0.1% 30.8% . . . 46 0.3% 60.9% 78 0.5% 55.1% 15 0.1% 53.3% 1 0.1% 0.0% 2 0.2% 0.0%

Credit Institutions 14 0.1% 64.3% 15 0.1% 40.0% . . . 2 0.0% 50.0% 67 0.4% 43.3% 7 0.1% 42.9% 1 0.1% 100.0% 1 0.1% 0.0%

Rubber and Miscellaneous Plastic Products 44 0.5% 65.9% 67 0.6% 80.6% . . . 342 2.5% 78.7% 98 0.6% 73.5% 39 0.4% 64.1% 8 0.5% 75.0% 2 0.2% 100.0%

Commercial Banks, Bank Holding Companies 7 0.1% 28.6% 10 0.1% 20.0% . . . . . . 19 0.1% 68.4% 5 0.0% 40.0% . . . . . .

Health Services 18 0.2% 44.4% 22 0.2% 54.5% 1 0.1% 0.0% 13 0.1% 46.2% 31 0.2% 25.8% 21 0.2% 23.8% 8 0.5% 50.0% 3 0.3% 100.0%

Hotels and Casinos 13 0.1% 76.9% 1 0.0% 100.0% . . . 1 0.0% . 14 0.1% 42.9% 5 0.0% 60.0% . . . . . .

Amusement and Recreation Services 29 0.3% 44.8% 15 0.1% 53.3% . . . 9 0.1% 33.3% 37 0.2% 54.1% 9 0.1% 33.3% 1 0.1% 100.0% . . .

Aerospace and Aircraft 13 0.1% 69.2% 60 0.5% 80.0% 1 0.1% 100.0% 213 1.5% 81.7% 48 0.3% 81.3% 87 0.9% 72.4% 11 0.6% 63.6% 3 0.3% 100.0%

Miscellaneous Manufacturing 140 1.5% 33.6% 24 0.2% 41.7% . . . 218 1.6% 55.5% 124 0.7% 44.4% 40 0.4% 40.0% 7 0.4% 85.7% 2 0.2% 50.0%

Paper and Allied Products 20 0.2% 40.0% 14 0.1% 57.1% . . . 224 1.6% 73.2% 52 0.3% 63.5% 9 0.1% 77.8% 3 0.2% 33.3% . . .

Advertising Services 3 0.0% 33.3% 3 0.0% 66.7% . . . 2 0.0% 50.0% 118 0.7% 56.8% 6 0.1% 50.0% . . . 2 0.2% 100.0%

Public Administration 125 1.3% 39.2% 6 0.1% 66.7% 1 0.1% 0.0% 17 0.1% 47.1% 53 0.3% 49.1% 9 0.1% 55.6% 2 0.1% 50.0% 1 0.1% 0.0%

Table 7Frequency of Joint Ventures by Industry and Type

% JVs w/

cross-

border

participants

N% of

all

% JVs w/

cross-border

participants

% of

all

% JVs w/

cross-

border

participants

N% of

allN

% of

all

% JVs w/

cross-border

participants

N

Marketing Agreement R&D Agreement Supply Agreement EquipmentLicensing Agreement Technology Agreement Exploration Agreement Manufacturing

N% of

all

% JVs w/

cross-

border

participants

N% of

all

% JVs w/

cross-

border

participants

N% of

all

% JVs w/

cross-border

participants

N% of

all

% JVs w/

cross-border

participants

39


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Agriculture, Forestry, and Fishing 18 0.2% 55.6% 18 0.2% 55.6% . . . 62 0.4% 80.6% 43 0.3% 69.8% 38 0.4% 47.4% 7 0.4% 42.9% . . .

Retail Trade-Eating and Drinking Places 24 0.3% 75.0% 1 0.0% 100.0% . . . 8 0.1% 62.5% 44 0.3% 52.3% . . . 5 0.3% 80.0% . . .

Sanitary Services 21 0.2% 42.9% 30 0.3% 50.0% . . . 15 0.1% 80.0% 29 0.2% 48.3% 18 0.2% 66.7% 8 0.5% 50.0% . . .

Soaps, Cosmetics and Personal-Care Products 33 0.4% 45.5% 19 0.2% 68.4% . . . 146 1.1% 86.3% 83 0.5% 72.3% 20 0.2% 70.0% 4 0.2% 50.0% 1 0.1% 0.0%

Wood Products, Furniture, and Fixtures 8 0.1% 25.0% 7 0.1% 85.7% 1 0.1% 100.0% 156 1.1% 72.4% 40 0.2% 67.5% 5 0.0% 60.0% 4 0.2% 75.0% 1 0.1% 0.0%

Retail Trade-Home Furnishings 11 0.1% 45.5% 5 0.0% 40.0% . . . 8 0.1% 50.0% 76 0.4% 61.8% 3 0.0% 0.0% 7 0.4% 71.4% 3 0.3% 33.3%

Retail Trade-General Merchandise & Apparel 28 0.3% 35.7% 3 0.0% 66.7% . . . 12 0.1% 50.0% 104 0.6% 66.3% 2 0.0% 0.0% . . . . . .

Educational Services 2 0.0% 50.0% 6 0.1% . . . . . . . 4 0.0% 25.0% 6 0.1% 50.0% 1 0.1% 0.0% . . .

Repair Services 3 0.0% 100.0% 1 0.0% 100.0% . . . 10 0.1% 70.0% 18 0.1% 66.7% 7 0.1% 42.9% 1 0.1% 100.0% 1 0.1% 100.0%

Retail Trade-Food Stores 7 0.1% 71.4% 1 0.0% 100.0% . . . 7 0.1% 100.0% 69 0.4% 84.1% 3 0.0% 33.3% 2 0.1% 50.0% . . .

Other Financial 6 0.1% 16.7% 10 0.1% 40.0% . . . 1 0.0% . 11 0.1% 54.5% 3 0.0% 100.0% . . . 1 0.1% 0.0%

Leather and Leather Products 24 0.3% 33.3% 7 0.1% 42.9% . . . 67 0.5% 65.7% 29 0.2% 65.5% 2 0.0% 0.0% 1 0.1% 100.0% 1 0.1% 0.0%

Miscellaneous Services . . . . . . 2 0.1% 0.0% 1 0.0% 100.0% 19 0.1% 31.6% 5 0.0% 20.0% . . . . . .

Tobacco Products 1 0.0% 100.0% 1 0.0% 100.0% . . . 49 0.4% 95.9% 13 0.1% 92.3% 1 0.0% 100.0% 1 0.1% 100.0% . . .

Holding Companies, Except Banks . . . 2 0.0% 50.0% . . . 1 0.0% 100.0% 2 0.0% 50.0% 1 0.0% 0.0% . . . . . .

Social Services . . . 1 0.0% . . . . . . . 7 0.0% . . . . . . . . . .

Legal Services . . . . . . . . . . . . 2 0.0% 100.0% . . . . . . . . .

Personal Services 3 0.0% 66.7% 2 0.0% 50.0% . . . 2 0.0% . 7 0.0% 42.9% . . . . . . . . .

Savings and Loans, Mutual Savings Banks 1 0.0% . . . . . . . . . . . . . . . . . . . . . .

No Industry Classification & Non-classifiable 273 2.9% 61.2% 278 2.5% 77.3% 11 0.6% 72.7% 356 2.6% 75.8% 516 3.0% 63.6% 328 3.2% 47.9% 97 5.6% 54.6% 19 2.1% 57.9%

Total 9352 100% 11241 100% 1865 100% 13780 100% 17183 100% 10104 100% 1721 100% 887 100%

Average 53.5% 63.5% 56.7% 70.7% 60.9% 49.5% 62.7% 57.4%

Correlation 0.622 0.965 0.352 0.912

40

(c)-(k) (d)-(l)(a)-(i) (m)-(o)


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1st Nation of the JV's operations N % Cum % N % Cum % N % Cum % N % of all Cum % N % of all Cum %

United States of America 22941 38.0% 38.0% 7402 20.9% 20.9% 15196 67.1% 67.1% 18028 52.8% 52.8% 4913 18.7% 18.7%

China 4141 6.9% 44.8% 3710 10.5% 31.3% 407 1.8% 68.9% 535 1.6% 54.3% 3606 13.7% 32.4%

Japan 4006 6.6% 51.4% 2756 7.8% 39.1% 1204 5.3% 74.2% 2674 7.8% 62.2% 1332 5.1% 37.5%United Kingdom 2459 4.1% 55.5% 1564 4.4% 43.5% 856 3.8% 78.0% 1172 3.4% 65.6% 1287 4.9%

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