Transnational or Social Capital? Returnee Versus Local Entrepreneurs1

by

Wilfried R. Vanhonacker

Professor of Marketing and Department Head, School of Business and Management, Hong Kong University of Science and Technology

David Zweig

Professor, Division of Social Science, Director of Center on China’s Transnational Relations, Hong Kong University of Science and Technology

and

Siu Fung Chung

Instructional Assistant, Division of Social Science, Hong Kong University of Science and Technology

Center on China’s Transnational Relations*

Working Paper No. 7

The Hong Kong University of Science and Technology Revised: May 2005

* Corporate Sponsor 2005-2006: Mr. Andre S. Chouraqui, Chairman DARTON Ltd - SMERWICK GROUP OF COMPANIES

Introduction

What is the impact of internationalization on the development of the private sector in China?

While China’s entry to the WTO built enormous pressure in China for expanding the private

sector (Lardy, 2002), particularly in areas such as the privatization of state-owned enterprises

(SOEs) or the emergence of private foreign trade enterprises, a new phenomenon has brought

together privatization and internationalization: the emergence of private firms run by

mainland entrepreneurs who returned from studying and/or working overseas (Wei, 2002;

Ben, 2002). Returned entrepreneurs bring back global networks, knowledge of overseas

markets, foreign technologies, and international management experience. Their strategic

perspectives may reflect overseas business attitudes more than domestic views about

management. They could, therefore, have advantages over people who did not go overseas.

But does training in a Western business environment translate into success in an Asian

one? While returnees may have earned what we call “transnational” capital—the value

added to one’s human capital that accrues from time spent, networks established, and

knowledge acquired, overseas—is it an advantage in China’s internal and external markets?

Can returnee entrepreneurs establish successful business networks in China and translate the

value added gained overseas into success in China’s complex business and political

environment?

This paper compares two groups of private entrepreneurs—those with foreign

educational or professional experience and those who were locally trained in order to answer

these questions. This comparison allows us to measure the impact of overseas study and

global experience on the development of the private sector and private enterprises in China. It

may also help us understand the future of China’s global economic links and its ability to

compete in the international economy.

1

Since 1978, over 700,000 mainland Chinese have gone overseas to study. But for many

years, the bulk of these scholars did not return. And those who did return were in large part

visiting scholars who did not undergo graduate education overseas (Zweig, 2002). While the

impact of these early returned entrepreneurs was significant on the development of the

education system and the R&D sector in China, they had only limited impact on the industrial

(private or public) or technological sector.

Since 1995, the number of returnees has increased at a yearly rate of about 13 percent.

Many of these returnees have graduate degrees, including a high percentage of PhDs and

MBAs. Also, changes in the global and domestic context since 1997 brought more returnees

to China. In 1997, leadership in China passed smoothly from the Deng Xiaoping generation

to the Russian Returned generation led by Jiang Zemin. In 1998, the “dot-com” boom hit

China, while in 1999, at the second session of the Ninth National People’s Congress, the

private sector was no longer seen as ancillary to the state-sector but was heralded as “an

important, integral part of China’s socialist market economy.” Finally, in fall 2001, China

joined the WTO, increasing the integration between China’s global and domestic economies.

These events led to a significant rise in the number of returnees with advanced technical

knowledge, who established themselves as private entrepreneurs. According to officials in the

Shanghai Personnel Bureau responsible for monitoring the returnees, there were over 2000

foreign trained entrepreneurs running private businesses in Shanghai in 2002 and the rate has

increased rapidly (Personnel, 2002). A preliminary survey in 2001 of 66 returnees working in

development zones in China found that 41 percent (27/66) had a foreign PhD, while 66

percent (44/66) were running their own businesses (Zweig, et. al., 2004). Western media has

recognized the importance of this group (Chea, 2002), but scholarly analysis has lagged,

largely because of the newness of this trend and the difficulties in studying them.

2

Key Theoretical Issues and Hypotheses

The core issue in this paper is whether “transnational” or “social” capital best explain

the performance of entrepreneurs in China. International forces have been playing a more

important role in China’s economic development (Zweig, 2002; Lardy, 2002); therefore,

people with “transnational capital”—defined as, value added to human capital by time spent

overseas, including foreign knowledge, technology, networks and resources--should do well,

relative to people who have not been abroad. Yet the impact of international forces on a

country’s developments is constrained by domestic structures, norms and conditions of the

society into which they are being transferred (Garrett and Lange, 1996; Deutsch, 1966).

Can managerial skills learned overseas, technology garnered overseas, and networks

established overseas guarantee success more than social capital accumulated by people who

did not go abroad but built up domestic business and political networks? According to Wank,

private entrepreneurs in China engage in “symbiotic corporatism,” giving local government

officials, and their families, special business opportunities in return for easier business

relations (Wank, 1995).2 Other studies have shown that social capital, in the form of

membership in the Chinese Communist Party (CCP), are among the best predictors of

household income or upward mobility in Maoist and post-Mao China (Cook, 1998; Bian, et.

al., 2001; Walder, et. al., 2000). Returnees may lack many of these political connections.

Finally, neither form of capital may be definitive in explaining success; in the Chinese

context, both local and returned entrepreneurs may have to build up their social capital to

succeed within China; and, both groups may succeed, or fail, at it in equal amounts. For

example, according to one report, 20 percent of start-up companies run by returnees fail

within the first year; another 70 percent just make ends meet; and, only 10 percent continue

to grow rapidly. However, this observer found similar results for local entrepreneurs (Ming

2002). Therefore, the core difference among our entrepreneurs may be their “human

3

capital”—i.e., their level of education, training, social background, age and gender. Walder et.

al. found that even in Maoist China, education was as important as ties to the CCP in

explaining career paths (Walder, et. al., 2000). According to Becker, “In the New Economy

and our technologically more advanced world, skills conferred by college education have

become more important. Although other factors may be at work, there are remarkable returns

to be seen now” (Manville, 2001).

To shed light on these issues, we sought answers to three broad research questions.

First, how much advantage is gained by returnees due to their overseas experiences? Are

there serious returns to their “transnational capital?” To what extent does access to foreign

technology enhance the performance of entrepreneurs? While some assert that returnees earn

advantages from “symbolic capital,” whereby institutions in China grant them advantages

because it is assumed that they are better (Hayhoe and Sun, 1989), we assert that time

overseas, the quality of technology, possessing a foreign degree or an overseas network, all

give returned entrepreneurs serious advantages in China’s ever-increasing international

market. And, even if the returnee does not engage in foreign trade, possessing a new

technology should supply important “rents” or “extra-normal profits” within the domestic

market due to the shortage of that technology within China (Tolinson, 1982).

Second, do returnee entrepreneurs manage the domestic environment, particularly their

relations with the government, differently than local entrepreneurs? Do they respond

differently to the politics of doing business in China? One hypothesis is that, since returnee

entrepreneurs have weaker social capital, but often set up shop in high tech incubators run by

local governments, they rely more on the local government, particularly in the formative

phase of their enterprise, than local entrepreneurs who, with stronger networks, eschew

government support and involvement.

4

Related to this last issue is the question of whether returnees use different management

styles due to their time overseas and whether this affects their level of performance? While

local Chinese private firms are likely to rely on social capital--ascriptive, rather than

professional, relations—in fundraising, management and sales/suppliers, do returnees run

their firms in a different way? Or is dependence on social capital necessary for success in

China’s personalized market (Solinger, 1991)?

Finally, we may find that transnational capital plays little role, and that returnees are just

as likely as locals to rely on social capital in the form of relatives, friends and government

ties. To that extent, human capital, in terms of the qualities that they, as individuals, possess,

may be the most important predictors of their firms’ level of success.

Methodology and Sampling Procedures

We created our database through face-to-face interviews with 200 firms: 100 run by

returnees and 100 run by local entrepreneurs. To do our survey, we collaborated with the

Chinese Private Enterprise Association (Zhongguo siying qiye xiehui) and its director, Zhang

Houyi. Team members on the Chinese side included Dai Jianzhong, of the Beijing Academy

of Social Sciences, and Dr. Chen Guangjin, of the Chinese Academy of Social Sciences. Each

was responsible for interviews in Guangzhou, Beijing and Shanghai, respectively. Overall,

we tried to insure diversity in sectors, including manufacturing and services. We also wanted

returnees working outside the IT sector, particularly in manufacturing, as we hypothesized

that returnees would excel at IT but be less effective than locals in manufacturing. Two other

criteria were imposed on the sample—the firms had to have over one million RMB in

revenue—otherwise we could not analyze their marketing strategy—and second, they had to

have been in business for two years or more. Overall, the vast majority of people interviewed

met these criteria.

5

Throughout the data collection, we tried to get large lists of returnees so we could select

from them randomly. In Beijing, we approached the External Relations Department of the

Beijing Science & Technology Commission. But while they had data on how many returnees

there were in the 14 high tech zones established for returnees in Beijing, they did not have a

comprehensive list of returnees in those zones. Also, too many firms on their list were in IT,

and we wanted more diversification in the nature of our enterprises. So, we turned to the

Returnee Association (gui guo renyuan xiehui) under the Industrial and Commercial

Association (gong shang ye lianhehui)—the former Industrial and Commercial

Bureau—which had a membership list of 350 people. From that list we chose 90 people in

three different returnee incubators (chuanye yuan) and sent them letters requesting an

interview. Our goal of 34 interviews was achieved after 80 people had been contacted,

yielding a success rate of 42.5 percent.3 In each zone we also asked officials to introduce us

to 30 local entrepreneurs. Among the locals, we had an acceptance rate of 64 percent (it took

50 contacts to get 34 locals who were interviewed).

Shanghai, and Guangzhou were more difficult. In Shanghai, we received 29 names from

the director of the Overseas Students Service Centre in Pudong’s high tech zone. After one

month, we had completed just 15 interviews. We went back to the director who gave us

another 37 names, allowing us to complete 33 interviews. The response rate, therefore, was

50 percent (33/66).

In Guangzhou we had more difficulties. While the head of the Guangzhou Returnees

Association (Guangzhou liuxue gui guo renyuan xiehui) was helpful, the people he put us in

contact with in the zones were less so. We worked with returnee service centers (liuxue

guiguo fuwu zhongxin) in two urban districts, Huangpu and Zhongshan. After some

hesitations, they gave us 40 names; from that list we arranged only six interviews, as many

returnees were out of town. Zhongshan officials then gave us another 20 names, but Huangpu

6

officials would not, asserting that the success rate would be equally low. So, the director of

the Guangzhou Returnees Association introduced us to the Tianhe Software Zone, which

gave us 25 names. Finally, through additional informal contacts, we completed 33 interviews.

In the end, we contacted 95 people to get the 33 respondents—a response rate of 35 percent.

Sample Profile

Table 1 gives the profile of the 200 companies contained in the data set. Among the

local companies only 14 percent were located in a zone, while 46 percent of the returnee

companies were located in a zone. As for the year the companies were registered, 59 percent

of the non-returnee companies were registered prior to 2000, while only 37 percent of the

returnee companies were, making returnee companies younger (figure 1).

As for shareholding structure, there is great variance within both subgroups; but on

average there is no significant difference in terms of equity held by the entrepreneur (at the

start of the company and now). However, there is a difference in the nature of the relationship

between the entrepreneur and the other shareholders in the company. For returnee companies,

37 percent have no ascriptive ties with other shareholders, whereas only 18% of local

companies have these types of ties. Although family, friends and classmates are shareholders

in both subgroups, more professional relationships exist between shareholders in returnee

companies than in local companies, where ascriptive ties may dominate.

Table 1 shows extensive reliance on personal funds and those of friends and family;

other sources of external financing were limited. Privately earned income is by far the

primary source of initial investment for both groups. For returnees, this 65% is income earned

abroad; for locals, 64% are monies earned in China. Family and friends are important

secondary sources of finances for both returnees and locals, but the role of schoolmates and

7

friends is more important for locals than returnees. Local governments are investing in

returnee firms—probably through the management company that runs the incubator in the

Table 1. Profile of Companies

Returnee Companies Local Companies

Located in Zone Yes 46% 14% No 54% 86% Company Age Since Founding

Before 1990 Before 2000 After 2000

2% 37% 61%

6% 59% 35%

Shareholders Number at start (range) 3 (1-8) 2 (0-7) Number now (range) 3 (0-10) % equity held at start (range) 61 (5-100) % equity held now (range)

58 (1-100) 59 (1-100) 61 (5-100)

Relationship

- immediate family - close family - friends, schoolmates - no special relationships

19% 12% 60% 37%

19% 16% 56% 18%

Source of Initial Financial Investment (% of investment funds) 1st 2nd 3rd 1st 2nd 3rd

1 Foreign-earned income 65 4 8 3 1 0 2 China-earned income 11 35 6 64 16 7 3 Family members 8 27 14 15 41 24 4 Schoolmates/friends 1 12 31 9 16 42 5 Local government 1 8 14 1 0 2 6 Venture capitalist 3 1 8 0 0 0 7 Domestic bank or company 5 5 14 7 21 18 8 Foreign bank or entrepreneur 4 4 6 0 0 2 9 (other) 2 3 0 1 4 6

Registered Capital (RMB 0000) (range) 511 (10-14000) 223 (2-5000) Employees (range) 54 (3-500) 74 (4-900) Turnover (RMB 0000) (range) 774 (11-6000) 851 (0-20000)

Customer Profile Retail 12% 22% Industrial: 88% 78% Mostly Foreign Companies in China 20% 13% Mostly Chinese Private Companies 44% 65% Mostly SOEs 36% 22%

8

Relationship to Distributors

1 Former Employees 12% 19% 2 Classmates 18% 19% 3 Relatives 17% 21% 4 Childhood Friends 3% 10% 5 Same Locality 22% 24%

Relationship to Suppliers

1 Former Employees 12% 14% 2 Classmates 28% 24% 3 Relatives 15% 18% 4 Childhood Friends 19% 14% 5 Same Locality 15% 16%

zones, while for locals, only domestic banks, SOEs, and private firms are an important third

source. Hence, very few non-returnees relied on local government financing when their

companies were created. Some, albeit few, returnees received private capital from abroad.

Table 1 also indicates to whom the firms sell and the importance of ascriptive ties to the

local sub-group. As we can see, 28% of returnees have no personal relations with their

distributors, while 93% of locals distribute their products through former employees (19% vs.

12%), former classmates (19% vs. 18%), relatives (21% vs. 17%), and childhood friends

(10% vs. 3%). Both sub-groups rely heavily on people who came from the same locality

(24% vs. 22%). As for customer profile, 88 percent of the returnees are in industrial markets

where 78 percent of the locals are. Accordingly, the large majority of entrepreneurs in both

subgroups are not in consumer goods. Looking at the profile of the industrial end-customer,

for both subgroups of entrepreneurs, Chinese private companies are the most important client

base. This is particularly the case for locals for whom 65 percent (relative to 44% for

returnees) of their client base are Chinese private companies. In contrast, returnees do more

business with foreign companies in China (20% of their client base relative to 13% for

non-returnees) and with SOEs (36% of their client base relative to 22% for non-returnees).

Table 2 profiles the human capital of the entrepreneurs themselves. The majority are

male (82% in both subgroups), and almost identical ages, despite the fact that the local

9

Table 2. Profile of Respondents

Returnees LocalsGender Male 82 82 Female 18 18 Age ≤ 30 8 11 31-40 45 43 41-50 38 38 51-60 8 8 > 60 0 0 Family Social Class Senior cadre 5 2 General cadre 21 20 Worker 17 40 Peasant 9 15 Intellectual/teacher 39 19 Businessman 6 2 Soldier 2 2 Other 1 0 Party Member Yes 17 20 No 80 79 No response 3 1 Years in leading management position in China (range)

1.83 (0-12) 4.43 (0-25)

Education in China Below High School

High School Diploma Technical College or Equivalent Undergrad Masters PhD

2 7

18 47 12 12

5 32 35 23 5 0

companies were established earlier than the returnee companies and that returnees spent more

time in university. There is a significant difference in social background. Returnees come

more from intellectual families, which is how they went abroad, while locals come more

often from worker or peasant families. Locals, relative to returnees, on average worked

longer in a leading management position in China; and given that the age distribution in both

10

sub-groups is the same, the different length of managerial experience for locals reflects the

time returnees spent abroad studying. In line with their social background, returnees attained

a higher-level of education in China; more than two-thirds of returnees finished university,

compared to less than one-third of locals. In terms of highest degree earned (in China or

abroad), 34 percent of the returnees received a PhD, while no locals did. Finally one measure

of social capital is whether they have joined the Communist Party, as membership in the

party has been shown to enhance networks and incomes. About 20 percent of entrepreneurs

in both subgroups were Communist Party members, which for returnees was surprisingly

high.

Table 3. Returnees Abroad

Quality of Technology

Returnees Locals

Internationally the latest technology 34 9 Not the latest internationally, but new for China

46 30

Not latest for China, but new for the region

8 24

Not the latest even in the region 5 31

93 94 Work Experience Abroad: Postdoc

Practical Work Experience None

7% 81% 12%

Skill Developed Abroad Teaching

Scientific Research Commercial R&D Sales and Marketing Human Resources Finance and Accounting Project Management Other

4% 50% 16% 21% 7% 4%

18% 19%

Importance of Overseas Experience to Business (Mean and St. Dev.) 4.39 (0.83)

Job Related to Skill Developed Abroad (Mean and St. Dev.) 4.22 (1.24)

11

Defining our Variables.

In this part of the paper, we analyze the transnational and social capital among our

entrepreneurs, highlighting important differences. Then in the subsequent section of the paper

we present our findings from three multiple regression analyses which compare the role of

these three forms of capital for the different sub-groups in explaining firm performance,

exports and revenues.

The Role of “Transnational Capital”

Did people who went overseas acquire “transnational capital” that can be measured

empirically and that could give them advantages in business? Transnational capital is derived

from overseas education, and, by definition, most returnees had acquired such capital. Among

our returnees, 26 percent had an overseas PhD, while 43 percent had an overseas MA. Seven

percent had a domestic PhD, but had worked overseas as a postdoctoral fellow. By definition,

locals had no overseas degrees, though some had been on short-term training programs

abroad. Like most entrepreneurs, who possess relatively low levels of formal education,4 37

percent of our local entrepreneurs never went beyond high school, and another 35 percent

only had a degree from a technical college or its equivalent. Thus our two groups of

entrepreneurs had significantly different levels of education and received that education in

very different locations.

Among returnees, 81 percent had practical work experience abroad. And while half of

the returnees had developed scientific skills abroad, a significant number supplemented that

training with a functional skill in management (commercial R&D, sales and marketing, HR

or project management). On average, returnees rated their experience abroad as extremely

important to their business (4.39 out of 5), and believed that the skill they developed abroad

12

was highly related to their current entrepreneurial work in China. They also believed that

foreign language skills were critical to their business (94% vs. 74%).

An important aspect of transnational capital is the quality of technology in one’s product

or firm brought from overseas. But what type of technology did they bring? If it was not

technology that is new for China, then there is little value to it. So, we asked our informants

whether their technology was: (1) internationally leading edge technology; (2) not

internationally leading edge, but new for China; (3) not new for China but new for their

region in China; or (4) not new even for their region. If the technology fits the fourth

category, they were relying primarily on marketing skills or their “social capital” to make

their business profitable; if the technology fit the first two characteristics, they were

employing their transnational capital. For the third type of technology, the perspective could

be mixed.

Our findings show that returnees possess a great degree of transnational capital (table 3).

They are four times as likely as locals to possess the latest international technology (34% vs.

9%), and almost 50 percent as likely (46% vs. 30%) to have technology that, while not the

newest internationally, is new for China. Thus while 34 percent of the returnees have a

product that, given China’s low labor costs, may be priced competitively in the international

market, fully 80 percent of returnee entrepreneurs have a technology that is new for China,

giving them a significant comparative advantage in the domestic market. Thus, this

technology could be an important explanation of their business success.

Local entrepreneurs, as expected, depend far more on social relations than the

technology in their product; while 26% (24/94) have a technology that is not new for China,

33% (31/94) have a technology that is “not new for their region.” If they are profitable, the

quality of service or personal ties must bring in the customers. As for the source of that

technology, only 16 percent of locals utilize externally developed technology as compared to

13

46 percent of returnees. Thus time abroad to master that technology could be a factor

increasing success. In fact, as shown above, their distribution network is based almost

entirely on ascriptive ties.

One hypothesis confirmed by the data is that technology brings people back to China,

precisely because they believe that it gives them an edge in the domestic market. When asked

why they returned to China, 27 percent of returnees selected “I have a technology that I

believe will have a good prospect in China” as their primary reason for returning, while

another 28 percent chose it as their second reason. For these entrepreneurs, technology drives

much of their activities.

Returnees’ overseas contacts have created a different pattern of business partners.

Among returnees, 67 percent had established a network of contacts while they were overseas,

but overall, returnees reported that they relied on their overseas network to a moderate level.

Still, 20 percent of returnees worked mostly with foreign companies operating in China, as

compared to 13 percent of locals. Some of these returnees may have been employed by these

foreign firms when they initially returned to China. Also, 17% of returnee firms have an

overseas subsidiary (5% for local companies). Returnees are more involved in exports than

locals (19% vs. 11%) and they expect to be more involved in exports five years down the

road (33% versus 21%). Returnees are also more likely to deal with the public sector than

local firms; 36 percent of them did most of their business with state-owned enterprises

(SOEs), as compared to 22 percent of locals, while the vast majority of locals (65%) did

business with other private firms, as compared to 41 percent of returnee entrepreneurs.

Social Capital: Entrepreneurs’ Local Government Relations

An entrepreneur’s ties to the local government are a good indicator of social capital

because successful entrepreneurs are portrayed as working closely with the government

14

(Wank, 1995). Yet, the need to rely on the local state may reflect a deficit in other forms of

social capital. For example, returnees may rely on government ties precisely because they

lack the social ties that facilitate competition in China’s personalized market (Solinger 1991).

Nevertheless, we asked entrepreneurs what was the best strategy to deal with the local

government in their location. We distinguished among five strategies, from having little or no

contact with the local government to taking the local government as a business partner.

Where 57 percent of the returnees indicated that establishing a cooperative relationship with

the local government was the best strategy (4 on a 5 point scale), 34% of the locals said so.

Among locals, 36% preferred to deal with the local government at arms length (i.e., little or

no contact or work with the local government when necessary and avoid becoming too

involved with them); the corresponding percentage for returnees was only 16 percent. Clearly,

returnees prefer to be more engaged with the local government, although few went as far as

taking them as an active partner (5th point) in their business (4%).

The opinions of the locals on how to deal with the government vary more widely. For

example, where 36 percent would want to keep the local government at arms length, 11

percent indicated that taking the local government as a business partner is the best strategy.

To some extent, this divergence might reflect their longer experience with local governments

(relative to returnees). Also the fact that most local companies in our sample are not located

in zones, where the local government plays a more active role, may also explain the different

levels of engagement.

We gauged the local government’s role in their businesses. Returnees indicated that the

local government had helped them with (a) finances, (b) land, office space and/or equipment,

and (c) import/export procedures. The local government had helped locals get (a) land, office

space and/or equipment, (b) suppliers, and (c) financial resources. Very few people in both

15

16

subgroups indicated that a government agency or government official had interfered in their

business (6 returnees and 5 non-returnees). Accordingly, it happens, but rarely.

We also looked at the entrepreneurs’ experiences with 23 bureaus, asking each to select

the five most important bureaus and to evaluate the quality (“rather positive” – “rather

negative”) of each of those relationships (table 4). For both subgroups, the Commercial and

Industrial Bureau and the Tax Bureau are the most important, but they are particularly

important for non-returnees, with virtually every local selecting them as being among the five

most important bureaus. Beyond these two, some differences arise. For entrepreneurs, the

Science and Technology Bureau is the third most important, which reflects the fact that

returnees work with more advanced technology than the locals, and that they often work in a

zone. For locals, the third most important bureau is the People’s Bank—33% of locals

received investments from local banks (table 1).

In terms of the quality of these relations, three significant differences emerge. For the

Personnel Department, the Office of New and High Technology, and the Office of the

Municipal Government Secretary, returnees have a more negative relationship than locals.

But for the three most important bureaus for either sub-sample, we see no significant

difference in the quality of the relationship between returnees and locals.

Looking at the quality of the relationships with the bureaus as a function of when the

business was registered, more positive relations exist among older businesses while more

negative relations exist for newer businesses; and, this pattern was much stronger for

returnees than for locals. Hence, returnees who had only recently registered the business were

particularly unhappy with their relations with the bureaus that were most important to them

and their businesses. In all likelihood, they were still uncomfortable with the administrative

style of Chinese officialdom, an issue often raised by returnees in other surveys.

Importance Rating Returnees

(n = 100) Locals (n = 100)

Returnees (n=100)2

Locals (n = 100)

t-test (significance)3

1 Personnel Department 301 15 3.10* 2.33 -2.81 (0.007) 2 Science and Technology Bureau 52 12 2.83* 2.33 n.s. 3 Finance Bureau 20 23 2.30 2.60 n.s. 4 Office for New & High Technology 45 19 3.07* 2.00* -3.65 (0.001) 5 Public Security Bureau 10 35 1.80* 2.20* n.s. 6 Education Bureau 3 4 2.33 1.75 n.s. 7 Foreign Affairs Bureau 8 3 2.38 2.00 n.s. 8 Economic and Trade Bureau 14 21 2.57 2.38 n.s. 9 Commercial and Industrial Bureau 75 93 2.43 2.37 n.s. 10 Tax Bureau 76 96 2.43 2.36 n.s. 11 Information Bureau 13 18 2.23 2.61 n.s. 12 National Development and Reform Commission 1 2 4.00 1.50 n.s. 13 People’s Bank, Branch 29 58 2.62 2.55 n.s. 14 United Front Department 3 0 4.00* - - 15 Overseas Chinese Office 8 0 3.13 - - 16 Bureau of Foreign Trade-Import/Export Office 10 6 2.10 2.17 n.s. 17 Patent Office 17 19 2.53 2.42 n.s. 18 Incubator Center Management Committee 6 1 2.83 2.00 n.s. 19 Land Bureau 4 3 2.75 2.00* n.s. 20 Customs office 23 23 2.35 2.48 n.s. 21 Foreign exchange office 15 3 2.13 1.67 n.s. 22 Office of local party secretary 2 2 2.50 1.00* n.s. 23 Office of municipal government secretary 17 36 2.59 1.92* -2.38 (0.024) 1 Number of respondents indicating that bureau was one of the five most important for them. 2 For those for which bureau was important, mean rating of their relationship with the bureau (1 = rather positive, 4 = rather negative). An “*”indicates whether the mean score is significantly different from 2.5 at α=0.10 or higher.

17

Table 4. Entrepreneurs’ Relations with Different Government Bureaus

3 Two-sided t-test on mean ratings between returnees and locals.

Both returnees and locals agreed equally that political support is necessary for them to

succeed. However, locals agreed significantly more than returnees with the statement “good

relations with government officials protects my business.” Hence, locals (more than returnees)

prefer good relations with the government (which in general they have), but nevertheless,

more than returnees, they prefer to keep the local government at arms length

Multivariate Analysis

Here we present the results of three different regressions, each of which had a different

dependent variable. But first, we outline our independent variables.

Independent Variables

We selected several indicators of “transnational capital” from our data set (table 5).

These include: the level of technology, number of years spent abroad, whether returnees

possessed an overseas degree or not, the importance of their overseas experience to their

business, whether or not they had an overseas subsidiary, and the level of reliance on their

overseas network. We also considered whether their current job is related to what they

studied overseas, since it is possible that they have not activated their transnational capital in

any significant way.

Indicators reflecting social capital encompass reliance on family, friends and the local

government. From our survey we included: whether family or friends invested in the

company, whether the entrepreneurs relied on personal relations when selecting their

distributors and suppliers, the source of financing, whether or not they are a member of the

Communist Party, and the nature of their government relations. In the latter case, we created

a single measure by taking the average score, in terms of the quality of the relationship, for

the five most important government relationships that each entrepreneur selected.

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Table 5. Variables and Coding

Variables Coding (Scales)

Dependent Variables: (1) Performance Conglomerate scale using factor scores from the

seven performance measures (2) Revenues Revenues in RMB 10,000. (3) Export Percent of revenues from exports Independent Variables: (1) Year registered Ordinal scale with 2004 = 1, 2003 = 2, … (2) Level of technology Ordinal scale with 1 = most advanced, 4 = not

the latest technology even in the region. (3) Transnational capital: - Time Spent Abroad Years, in total - Degree Abroad Dummy variable; 1 = yes, 0 = no. - Importance of Overseas Experience

to Business Ordinal scale; 1 = not important at all, 5 = very

important - Reliance on Overseas Network Ordinal scale; 1 = not at all, 5 = very much - Job Related to Skill Learned Abroad Ordinal scale; 1 = not at all, 5 = very much - Overseas Subsidiary Dummy variable; 1 = yes, 0 = no - Work Experience Abroad Dummy variable; 1 = yes, 0 = no (4) Social capital: - Friends/family as shareholders Dummy variable; 1 = yes, 0 = no - Friends/family as suppliers Dummy variable; 1 = yes, 0 = no - Friends/family as distributors Dummy variable; 1 = yes, 0 = no - Friends/family as financiers Dummy variable; 1 = yes, 0 = no - Government relations Ordinal scale; mean of ratings on 5 most

important bureaus; 1= rather positive, 4 = rather negative

- Strategy in dealing with government Ordinal scale; 1 = no contact at all, 5 = government as partner

- Member of communist party Dummy variable; 1 = yes, 0 = no (5) Human capital: - Age Ordinal scale; 1 if < 30, 5 if 61 ≥ - Gender 1 = male, 0 = female - Education 1 = below high school, 6 = PhD - Social class ISE scale - Years of management experience Years, in total

Finally, to measure the impact of the entrepreneurs’ human capital, we included: age,

gender, educational level, family’s socio-economic background, and years of management

experience. In total we had 21 variables, but in some cases there were missing data.

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Dependent Variables

In order to estimate the impact of transnational capital, social capital, and human capital

on the performance of the entrepreneurial firms, three regression models were estimated. One

dependent variable is a composite of the self-reported company performance.5 All 200

companies were assessed on the basis of 7 scales: (a) profitability/return on assets, (b) cash

flow, (c) sales growth, (b) market share, (e) technical product/service design and

development, (f) quality of product/service, and (g) employee satisfaction. The entrepreneurs

reported how important each of these scales was to them and how they were performing

relative to their industry average (a five-point scale with 1 = much lower than industry

average, and 5 = much higher than industry average). Hence, we need to keep in mind that

performance is “self reported,” or based on “self-evaluation.” Also, while some significant

differences were apparent in the market focus and marketing practices between returnees and

locals, those policies and their differences did not significantly impact self-reported

performance. Locals do not report significantly better performance than returnees; in fact,

both subgroups of entrepreneurs have a unique way of addressing the market but feel that

they are equally successful in doing so.

Our second dependent variable is total revenues, which again was self-reported. While

revenues need not reflect the health of a firm, as it could be running a huge deficit, we had no

other empirical indicator that was not heavily influenced by the informants’ biased view of

their own company. Finally, we used foreign trade as a share of total revenue as our third

performance indicator.

The Results6

Our findings are quite informative. As table 6 shows, seven variables were significantly

correlated with the self-reported performance of the firm at 0.10 or higher.7 For both locals

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and returnees, the age of the company was positively correlated with performance. This

finding is not surprising, suggesting that people who have been running their company for a

longer time, feel more positive about its accomplishments.

Table 7. Performance1

Independent Variables Parameter Estimate (Significance)

(1) Year Registered 0.056 (0.01) (2) Level of Technology -0.184 (0.00) (3) Transnational Capital: - Reliance on Overseas Network -0.158 (0.01) - Work Experience Abroad 0.606 (0.08) (4) Social Capital: - Friends/Family as Distributors 0.586 (0.05) - Friends/Family as Financiers -0.640 (0.09) (5) Differential Effects:2 D * Friends/Family as Suppliers 0.655 (0.09) Model Fit Statistics: R2 = 0.21 F-value (significance) = 1.84 (0.02) Condition Index3 = 11.96 1 Model with 21 variables; those significant at α = 0.10 or higher are shown. 2 With D = 1 for returnee, D = 0 for local. 3 Multicollinearity diagnostic.

Three transnational variables were significant. First, the level of technology was highly

correlated with “performance,” but since 1 was the highest level of technology, and 4 was the

lowest, the parameter estimate is negative. Thus even local firms did better if they had

technology that was world class or, at least, unique for China. This finding again reinforces

the assertion that global linkages are critical for success in an internationalizing China.

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A second transnational variable was an entrepreneurs’ reliance on an overseas network.

The findings suggest that the more returnees and locals rely on overseas networks, the less

positively they view their firm’s performance. This confirms the hypothesis that overseas

networks are not enough and that returnees recognize that they must sink their feet in the

domestic market if they are to succeed. Finally, overseas work experience is weakly

correlated with performance (p>.07) for both cohorts, though locals had rather limited

overseas experience; otherwise they would have been scored as returnees.

Two aspects of social capital were correlated with the perceived performance of the firm.

Both locals and returnees who rely on ascriptive ties to develop their distribution networks

view their firm’s performance positively. While this finding is not surprising for locals, one

might think that returnees would have a negative view of relying on ascriptinve ties when

selecting distributors. Still, China’s market is what it is and returnees have to adapt to

succeed. In fact, while locals apparently do not need friends and relatives as suppliers to be

successful, returnees apparently do—perhaps reflecting their weaker market position and the

fact that getting access to quality goods in China’s domestic market may still depend on good

personal ties. Finally, among both groups, we find a correlation between relying on friends

and relatives for financial support and problems in performance. In fact, an earlier analysis

showed that local firms, who received finances from relatives, had difficulty keeping them

from interfering in the firm’s activities, and scored rather poorly on “worker satisfaction.”

Many variables used to explain the variations in revenues were also significant (table 8),

and the model itself is quite powerful (R2 = 0.39) in explaining the reported differences in

revenues. Reported revenues were highly correlated with the age of the firm for

both returnees and locals, which suggests that the link between age and performance,

reported above, was real and not just perceived. Among our transnational variables, the level

of technology was significant, albeit at the .09 level. Also, having an overseas subsidiary was

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positively correlated with revenues for locals, but negatively correlated for returnees. No

doubt, a local company that was able to develop an overseas subsidiary was doing

Table 8. Revenues1

Independent Variable Parameter Estimate (Significance)

(1) Year Registered 134.960 (0.00) (2) Level of Technology -217.313 (0.09) (3) Transnational Capital: Overseas Subsidiary 4272.858 (0.00) (4) Social Capital: Member of Communist Party 1612.984 (0.00) (5) Differential Effects2: D * Overseas Subsidiary -4545.277 (0.00) D * Member of Communist Party -1944.471 (0.01) Model Fit Statistics: R2 = 0.39 F-value (significance) = 4.66 (0.00) Condition Index3 = 10.59 1 Model with 20 variables; those significant at α = 0.10 or higher are shown. 2 With D = 1 for returnee, D = 0 for local. 3 Multicollinearity diagnostic.

particularly well, and probably had a lot of revenue, which allowed it to reach out overseas.

This finding fits well with the Chinese government’s policy of encouraging successful

domestic firms to do business overseas (zou chu qu). But it remains difficult to understand

why having an overseas subsidiary would lead to lower revenues for a returnee. Perhaps if

their overseas subsidiary was their original firm, they were expending too much of their

energies (and capital) to keep it going.

Interestingly, only one social capital variable was significant but it is very important.

Being a member of the Chinese Communist Party (CCP) enhanced the revenue of a local firm

23

yet harmed revenue for returnees. In the latter case, returnees who were CCP members may

have been poor businessmen or were constrained, in terms of “black” or “gray” market

activity, by punishments they might receive, as party members, for corruption.

Only one variable—having an overseas subsidiary—is correlated with exports, and the

levels of significance are .00 and .01 for locals and returnees, respectively. However, such a

finding is not surprising, so we do not present it in tabular form. Any local with an overseas

subsidiary should be an active exporter, unless the subsidiary is a front for laundering money

overseas. In any case, the model for this regression is highly significant with an R2 = 0.36.

Finally, it is worth noting which variables are not significant. For example, level of

education, gender, and length of time spent abroad do not affect the reported performance or

revenues, though work experience abroad does. Also, neither the strength of ties to the local

government nor the strategy employed to deal with the government, affects the revenue or

performance of these firms. We would have anticipated some relationship, as returnees often

need the government’s support to succeed in the early days. Yet table 4 showed that there

were only minor differences in the nature of the ties to the government between locals and

returnees, which explains why there is little impact on our indicators of success.

Conclusion

What can we say about our original hypotheses? First, returnees, more than locals,

work closely with the government, a finding that runs counter to our expectations. We

assumed that local private businessmen have woven a closely-knit web with the local state as

a form of protective guanxi (Wank, 1995). But, in fact, local entrepreneurs keep their distance

from the government, despite having good relations with it. But returnees, particularly those

in the zones, depend on the local state for capital, land, and labor. As returnees to a China that

has been transformed since they left, they need the help of various government bureaus to get

24

started. Still, they remain uncomfortable with “capitalism with Chinese characteristics,” i.e.,

having to work closely with an annoying bureaucracy.

Second, technology is bringing people back, in anticipation that this form of

“transnational capital” will facilitate success and the data support this hypothesis. We found a

strong relationship between level of technology and subjective measures of success, but this

was true for both returnees and locals. The findings also support the argument, however, that

high quality technology is not enough to succeed in China’s politicized domestic market.

Even returnees need to establish personal ties to insure the supply and distribution of their

products.

The result is that social capital is very important for all entrepreneurs. Local ones report

that despite having technology that is not unique for China—they can succeed. Hence their

social capital must be important. On the other hand, advanced world-class technology is not

enough to guarantee success for returnees in the domestic market; they need ascriptive ties.

But those ties must be personal, not ties to the government, as relations with the local

government do not explain any of our success indicators.

Social capital, in the form of membership in the Chinese Communist Party, is very

important for the success of our entrepreneurs. These findings mirror studies of political

capital in China, which show that being a CCP member or having a CCP member in one’s

family contributes to one’s income or life chances, even if the reform era. Still, for returnees,

this type of social capital is more of a liability, through further research is necessary to

explain why. And for both returnees and locals, social capital is problematic if family and

relatives, who invest in the firm, interference in its management and thereby generate low job

satisfaction among employees.

Still, bringing a new technology into China is an important path to enrichment and

remains a major force for returning. Such a finding is clearly a benefit to the Chinese

25

government which can spread this message as a way to attract more returnees, more foreign

technology, and thereby upgrade the quality of the domestic market. By rewarding those who

bring in technology, the government (and the Chinese market) are clearly creating the

appropriate environment for China’s opening to create a more technologically advanced

Chinese state.

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Endnotes 1 Research funds for this paper were provided by the Hang Lung Center, Hong Kong University of Science and Technology. Research assistance was provided by Vivian Lam. 2 A brief review of these various perspectives and empirical findings can be found in the chapter by Bian and Zhang in this book. 3 Returnees had a much higher refusal rate than locals, something that went against our expectation. Returnees are generally quite amendable to talk about their experiences. In this case, however, many returnees were on business trips out of town if not out of country. 4 Overall, domestic entrepreneurs have less education than returnees. However, according to national surveys, their level of education has increased significantly throughout the 1990s. Thus while only 16.6 percent had a university education in 1993, by 1999, 35 percent did. See Zhongguo siying jingji nianjian, 2000, p.362, cited in Gilles Guiheux, 2002., “The Social Profile of Private Entrepreneurs: Socio-Economic Diversity and Proximity to the Party State,” paper presented at the conference on “State Reforms and Social Stability in China,” July 5-6, 2002, Chinese University of Hong Kong. 5 The first measure, a conglomerate performance measure, was derived from the single factor solution to a factor analysis of the seven performance measures included in the questionnaire.

6 For those variables for which we have observations for returnees and locals, a slope dummy was introduced. For the independent variable X, we specified the model as (α+βD)X where D is a dummy variable indicating whether the observation was for a returnee (D=1) or a local (D=0). The α parameter measures the pooled effect of variable X when β=0 or the effect of variable X for locals when β≠0; the corresponding effect of variable X for returnees would then be (α+β). The parameter β measures the differential effect of variable X for returnees. In estimating the three models, we used multicollinearity diagnostics to derive the final model. We took extreme care to drive the condition index to a value of 10, considered a relatively low level of multicollinearity. We did this by dropping highly correlated independent variables. The resulting models are reported here, focusing on the parameter estimates significant at 0.10 or higher. 7 The condition index for the final model equals 11.96, and the corresponding model retained 21 variables. The model is significant at the 0.02 level, and the R2=0.21.

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