Transnational or Social Capital? Returnee Versus Local Entrepreneurs 1 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
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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
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
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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)
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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
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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
(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.
21
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
22
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
(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.