New evidence from multinational pharmaceutical firms’ FDI into China

Sequence of FDI entry mode decision making process: new evidence from multinational pharmaceutical firms’ FDI into China

Fuming Jiang

ABSTRACT

Based on Jiang’s (2003) eclectic framework and the survey database established in 1999, this paper conducted a more refined comparative analysis into the sequence of FDI entry mode decision making process in the context of international pharmaceutical firms’ FDI entry mode decisions into China by categorising firms according to different types of share of ownership, L e. firms with less than 50% share of ownership (Minority-JV), firms with equal share of ownership (Equal-JV), firms with greater than 50% share of ownership (Majority-JV), and firms with 100% share of ownership (SV) in their China ventures. The results suggested that joint venture (JV) differs significantly from sole venture (SV) entry mode, and three types of JV entry modes also differed substantially from each other, which suggested that it would be more appropriate to treat each type of JV entry modes as a real alternative for SV entry mode.

1. RESEARCH FOUNDATION

Most past studies on foreign market entry modes have emphasised “market imperfection (ownership advantage) theory” (Hymer, 1960 & 1976), “location specific advantage theory” (Franko 1971; Stopford and Wells 1972), “internalization theory” (McManus, 1972; Buckley and Casson, 1976), “transaction cost theory” (Williamson, 1975; Buckley and Casson, 1976; Casson, 1982; Caves, 1982; Anderson and Gatignon, 1986; Erramilli and Rao, 1993), “strategic behaviour approach” (Harrigan, 1985; Kogut, 1988) and “resource based theory” (Wernerfelt, 1984; Barney, 1986; Collis, 1991; Peteraf, 1993). Some recent studies have been trying to combine a number of theories into one-eclectic framework to explain the entry mode choice decision. Dunning’s (1988) “eclectic paradigm” denoted that the choice of entry mode decision is influenced by three types of factors: ownership-specific factors of a firm, location-specific factors of a market and internalization advantages of integrating transactions within the firm. Hill, Hwang and Kim (1990) developed their “eclectic theory of the foreign entry mode choice” by combining transaction cost theory, internalization theory and strategic behaviour approach. Bell (1996) created a new eclectic framework to exam Dutch firms’ entry mode decision by adding resource based theory into Hill, Hwang and Kim’s (1990) eclectic mode.

Following Stopford and Wells’s (1972) pioneering study on entry mode choice decision between SV and JV using the Harvard Multinational Enterprise Database, a number of important empirical studies have been conducted. These empirical studies revealed that the probability of setting up SVs is positively related to the level of the parent firms’ international experience (Gatigon and Anderson, 1988; Erramilli, 1991; Agarwal and Ramaswami, 1992; Benito, 1996), host country experience (Stopford and Wells, 1972; Gomes-Casseres, 1989 and 1990; Padmanabhan and Cho, 1996), parent firm size (Gomes-Casseres, 1990; Agarwal and Ramaswami, 1992; Benito, 1996), marketing intensity of parent firm (Stopford and Wells, 1972; Gatigon and Anderson, 1988; Gomes-Casseres, 1989), research and development intensity of parent firm (Stopford and Wells, 1972), asset specificity of parent firm (Gatigon and Anderson, 1988; Padmanabhan and Cho, 1996), and perceived market potential of the host country (Agarwal and Ramaswami, 1992). JV entry mode would be preferred when cultural distance is large between the host and the home countries (Agarwal, 1994; Benito, 1996; Barkema, Bell and Pennings, 1996). The probability of forming JVs is positively related with the level of host country welfare (Gomes-Casseres, 1989 and 1990), the level of host government restrictions (Fagre and Wells, 1982; Lecraw, 1984; Gatigon and Anderson, 1988; Gomes-Casseres, 1989 and 1990; Padmanabhan and Cho, 1996) and level of competition in the host country (Gomes-Casseres, 1990). Firms would be more likely to establish JVs when the firm enters into a research and development intensive industry (Kogut and Singh, 1988b), and a growth industry (Hennart, 1991).

The success of each foreign market entry is affected by many factors. Firms that want to invest in a foreign market need to consider the possible impacts of these factors (Bell 1996). Root (1994), and Mockler and Dolomite (1997) have elaborated on the factors affecting the decision choice of entry mode. They suggested that an initial concept of an entry mode can be determined by studying host country environmental, market, production, parent firm’s home country, parent firm’s product and resource commitment factors. However, Kumar and Subramanian (1997) deemed that the existing literature on the choice of entry modes into international markets is based on the assumption that the mode of entry choice is a function of various exogenous factors, but an alternate view could be that certain factors endogenous to the decision task affect the choice of mode of entry. This view holds that a decision made by a manager depends not only on the relevant external factors but also on characteristics of the decision task, characteristics of the manager, and the manager’s expectations about the quality of the information available to reach the decision as managers of multinational corporations may face time and resource constraints when making the decision. Jiang’s (2003) study, based on an eclectic mode by integrating Kumar and Subramania’s (1997) contingency model and Root’s (1994) and Meckler and Dolomite’s (1997) conventional model, into multinational pharmaceutical firms’ FDI entry mode decision into China found that firms who chose a joint venture, two external factors appeared to be the major determinants of this choice, namely China environmental factors and the market factors. Whereas, in the case of the firms who chose a sole venture, an internal factor appeared to be the major determinant, namely parent firm’s decision task related factors. However, the literature remains controversial in relation to the sequence of FDI entry mode decision making process. Bell (1996) suggested that Minority JV, Equal JV, Majority JV should not be treated as one group al an alternative to SV because they are genuinely different forms of organisation. This finding was in contrast with Gatignon and Anderson’s (1988) two-stage approach where firms decide whether they choose a JV or not, if so, then firms would select a specific JV operation. This paper, based on Jiang’s (2003) eclectic framework and the survey database established in 1999, conducted a more refined comparative analysis by categorising firms according to different types of share of ownership; i.e. firms with less than 50% share of ownership (Minority JV), firms with equal share of ownership (Equal JV), firms with greater than 50% share of ownership (Majority JV), and firms with 100% share of ownership (SV) in their China ventures. FIGURE 1 is an elaboration of the eclectic conceptual framework (Jiang, 2003), which explains the hypotheses relationships between the choice of FDI entry modes and seven groups of independent variables.

[FIGURE 1 OMITTED]

The hypotheses are formally stated below:

Hypothesis 1 (H1): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is negatively related to the importance of China’s environmental factors.

Hypothesis 2 (H2): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is negatively related to the importance of China’s market factors.

Hypothesis 3 (H3): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is negatively related to the importance of China’s production factors.

Hypothesis 4 (H4): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is positively related to the importance of the firm’s home country factors.

Hypothesis 5 (H5): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is positively related to the importance of the firm’s product factors.

Hypothesis 6 (H6): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is positively related to the importance of the firm’s resource commitment factors.

Hypothesis 7 (H7): The probability for a firm to choose an FDI entry mode with higher (or lower) level of share of foreign ownership is positively related to the importance of the firm’s decision task factors.

2. RESEARCH METHODOLOGY

2.1 The Population and Sample

A total of 117 foreign pharmaceutical firm invested pharmaceutical companies (IPFIPCs) in Mainland China during the period of 1980-1998 were defined as the population for the research. Over 84% of IPFIPCs were located in the east China’s 13 provinces and municipalities where the economic development had been reached relatively more advanced level. Less than 16% of IPFIPCs were distributed in China’s middle and west areas. A total of 98 IPFIPCs distributed in the three major regions in east China and which accounted for 83.76% of the population were defined as the sample size for this research. These IPFIPCs in the sample include 29 in South East Region (SER), 38 in Middle East Region (MER) and 31 in North East Region (NER). The SER comprises of Guangdong and Fujian provinces. The MER covers Shanghai municipality, Jiangsu, Anhui and Zhejiang provinces. The NER consists of Beijing and Tianjin municipalities, Liaoning, Shandong and Hebei provinces. The companies in the sample in SER, MER and NER were centred on Guangdong, Shanghai and Beijing, respectively (CCPIE, 1995; NTDB, 1996; MIMS Asia, 1998, SPGC, 1999).

2.2 Data Collection

A questionnaire was designed in both English and Chinese versions and was pre-tested with six pretesting respondents for the data collection. The research fieldwork was conducted in China between early April and late June in 1999. The data was collected through both personal interviews, and a mail questionnaire survey. Personal interviews were conducted with senior executives of foreign business partners in IPFIPCs in China, and the postal questionnaires were addressed to foreign general managers/representatives in IPFIPCs in China. In total 44 companies participated in this research, and 82% of answered questionnaires were obtained through personal interviews. Of the responding firms, 39 firms selected joint venture entry mode including 11 Minor-JVs, 7 Equal-JVs, and 21 Majority-JVs. The rest chose sole venture with 100% share of ownership. 3 companies including 2 in Guangdong and 1 in Jiangsu were found to have ceased operations during the fieldwork. Also 1 company in Guangdong had the foreign partner’s share sold to its Chinese partner before this survey was conducted. Therefore the real sample size was reduced from an estimated 98 to 94 IPFIPCs, which means that a 46.81% response rate was achieved.

3. DATA ANALYSIS RESULTS

3.1 Variable Coding and Scale Reliability

The dependent variable is FDI entry mode choice (3JVs and SV). Minor-JV, Equal-JV, Majority-JV and SV were coded as “1”, “2”, “3” and “4” respectively. The seven independent variables are China’s environmental factors, China’s market factors, China’s production factors, Parent firm’s home country/region factors, Parent firm’s product factors, Parent firm’s resource commitment factors and Parent firm’s decision task related factors. Independent variables were measured at ordinal level. The questions were designed using a 6-point Likert scale, ranging from “1” not important to “6” very important for each of the seven groups of factors. Respondents were requested to indicate their perceptions of the degree of importance of the seven groups of factors to their parent firms’ decisions in choosing an FDI entry mode for investing in China. The reliability of the scales was tested, and Cronbach’s alpha is used as the indicator. The internal consistency of the scale values for each one of the seven groups of factors is found to be at an acceptable level. The reliability coefficients (Alpha) for the seven groups of exploratory variables were 0.80 for ‘China environmental factors’ (28 items), 0.78 for ‘China market factors’ (9 items), 0.76 for ‘China production factors’ (14 items), 0.87 for ‘Parent firm’s home country/region factors’ (6 items), 0.66 for ‘Parent firm’s product factors’ (3 items), 0.70 for ‘Parent firm’s resource commitment factors’ (13 items) and 0.60 for ‘Parent firm’s decision task related factors” (5 items). Two levels of analyses were performed by means of multinominal logistic regression analysis followed by ANOVA. Logistical regression was used to detect which group/(s) of factors contributed most to the FDI entry mode choice decision. Total scores for each of the seven groups of factors that were used for the logistic regression were calculated respectively by summing up all the original scores for each single factor in each one of respective seven groups of factors.

3.2 Multinominal Logistic Regression Analysis

According to Gatignon & Anderson (1988) and Bell (1996), a more refined logistical regression analysis was carried out to find the best model for describing whether and how the impact of the seven groups of factors differed for the four levels of share of ownership; i.e. Minority JV, Equal JV, Majority JV, and SV. The SV was taken as the reference category, so that the effects of the independent variables on the three types of JVs were interpreted as relative to SV. Analogous to the binomial logistical model, the SV mode was taken as the base category, which implies that firms see the different types of JV as real alternatives for SV (Bell, 1996); i.e., when international pharmaceutical firms entering into China, firms were expected to make only one decision on entry mode that will be selected.

The results of multinominal regression analysis are presented in TALBLE 1. A positive [beta] coefficient means an increased probability of the specific type of JV entry mode relative to a SV entry mode, and a negative [beta] coefficient means an increased probability of a SV entry mode. The results suggested that China environmental factors had a significant effect on the probability to choose a Minority JV ([beta]=0.3228; p<.05), an Equal JV ([beta]=.3320; p<.05), and a marginally significant effect on the probability to choose a Majority JV ([beta]=0.2408; p<.10) over a SV. These mean that when China's environmental factors become an important concern to international pharmaceutical firms' FDI entry mode decision into China, firms would be more likely to choose JV entry modes rather than a SV. The impacts of China environmental factors on firms towards choosing a Minority JV and an Equal JV were greater than that on firms towards choosing a Majority JV. Therefore, Hl was supported.

An increased degree of importance of China market factors significantly increases the probability of Minority JV ([beta]=0.8756; p<.01) and Majority JV ([beta]=0.6558; p<.05) as opposed to SV. A marginal significant impact applies to Equal JV ([beta]=0.5992; p<.10). Investing firms prefer to choose JV entry modes for entering into the Chinese market when China's market factors was considered as the important parameter to their FDI entry mode decision. The impact of China market factors on firms towards choosing a Minority JV was greater than that on firms towards choosing a Majority JV, and even more so for choosing an Equal JV entry mode. H2 was supported by this finding. The results also show that when parent firm's decision task related factors become an important concern, SV is likely to be the preferred entry mode over an Equal JV ([beta] = -1.2128; p<.10) and a Majority JV ([beta]=-1.0485; p<.10). H7 was fairly supported by the finding. Statistically, there was not sufficient evidence to support hypotheses 3 to 6.

The overall multinomial logistic regression model classified 72.7 percent of observations correctly. The -2 log was 65.9687 and the model Chi-square was 43.079 (with df=21) and was significant at .01 level (p=.0030), which indicates a good fit of the model. The results of multinomial logistic regression analyses based on four levels of share of ownership closely resembled those of the binomial logistic regression analysis base on JV and SV (Jiang, 2003). All variables that were significant in the binomial logistic regression analysis were also significant for most types of JV entry modes in the multinomial logistic regression analysis. The only exception was that the directions of effects of China’s production factors on Minority JV and Majority JV, and the direction of effect of parent firm’s home/country/region factors were not expected and were not consistent with those revealed from the binomial logistical regression analysis. However, as indicated earlier, the impact of these two groups of factors on international pharmaceutical firms’ FDI entry mode choice were not significant. The multinomial logistic regression analysis also indicates that the effects of China environmental and market factors on international pharmaceutical firms’ FDI entry mode decisions were substantially different among the different types of JV. Therefore the three types of JV should not be considered as one group of format of ventures.

3.3 ANOVA Results

To scrutinise the differences among Minority JV, Equal JV, Majority JV and SV, an ANOVA procedure was carried out to investigate significant variables that differentiated Minority JV, Equal JV, Majority JV and SV. Post-hoc comparisons using Tukey HSD test (when equal variance within groups is assumed) and Games-Howell (when equal variance within groups is not assumed) were employed to investigate where the differences lie among the four groups of firms in scoring the seven groups of variables. The ANOVA results for significant variables are presented in TABLE 2 and TABLE 3.

The ANOVA analyses have indicated that China’s environmental variables including govemment policies and regulations, level of the Chinese government to deal with, role of the Chinese government in the economy, the status of economic co-operation between China and parent firm’s country/region, Chinese way of life, way of doing business in China, availability and quality of infrastructure, geographic proximity distance between China and parent firm’s country/region, China’s market variables including availability of marketing infrastructure, quality of distribution infrastructure, required cost of marketing effort and parent firm’s resource commitment variables including production skills and management capacity all had significant impacts on foreign pharmaceutical firms’ level of share of ownership in their China ventures. Firms that scored higher for China’s environmental and market variables tended to have lower level of share of ownership, and firms that scored higher for parent firm’s resource commitment variables tended to have higher level of share of ownership. SV firms differed significantly from JV firms, and the three types of JV firms also differed substantially from each other in perceiving the importance of the significant variables.

4. CONCLUSION AND DISCUSSIONS

This paper examined the sequences of FDI entry mode decision making process in the context of the international pharmaceutical firms’ investment in China. It suggested that the impacts of the significant variables on SV firms differed significantly from that on JV firms, and these results parallel those suggested by previously published results on the FDI entry mode choice between a SV and JV (Jiang, 2003). The three types of JVs also differed substantially from each other, which suggests that it would be more appropriate to treat the three different types of JV entry modes as real alternatives to the SV entry mode choice. This result was in a similar line with Bell’s (1996) finding, but in contrast with Gatignon and Anderson’s (1988) two-stage approach. The analyses have shown that China environmental and market factors were significant factors that affected international pharmaceutical firms’ decisions in choosing an entry mode among Minority JV, Equal JV, Majority JV and SV options. When China’s environmental factors became a significant concern to international pharmaceutical firms’ FDI entry mode decisions, international pharmaceutical firms would be more likely to choose a JV entry mode with minority or equal share of ownership rather than a SV, and a JV with majority of share of ownership also seems to be preferable over a SV entry mode. When China’s market factors became a significant concern to international pharmaceutical firms’ FDI entry mode decisions, international pharmaceutical firms would be more likely to choose a JV entry mode with minority or majority share of ownership rather than a SV. A JV entry mode with equal share of ownership also appeared to be a preferable entry mode over a SV entry mode. On the other hand, SV seems likely to be a preferred entry mode over JV entry modes with equal JV or majority JV, when parent firm’s decision task related factors became an important concern to international pharmaceutical firms’ FDI entry mode decisions. This research also revealed that an entry mode with higher level share of ownership would be preferred when parent firm’s resource commitment factors have significant impact on entry mode decisions. However, the application of the findings from this research may only be applicable to the certain industries as the population for this research was limited to the international pharmaceutical firms’ FDI in China. Future research into other industries would be necessary for forming a more comprehensive theoretical basis on the sequence of FDI entry mode decision making processes.

TABLE 1: MULTINORMINAL LOGISTIC REGRESSION RESULTS

China China

Entry environmental market

Modes Intercept factors factors

Minority JV (n = 11)

[beta] -15.0264 0.3228 0.8756

S.E. 22.7101 0.1399 0.3334

Sig. .5082 .0211 * .0086 **

Equal JV (n = 7)

[beta] -13.8224 0.3320 0.5992

S.E. 22.8374 0.1401 0.3139

Sig. .5450 .0178 * .0563 ([dagger])

Majority JV (n = 21)

[beta] -8.8520 0.2408 0.6558

S.E. 19.2998 0.1294 0.2950

Sig. .6465 .0627 ([dagger]) .0262 *

SV (n = 5) 0 0 0

Parent firm’s

China home country/ Parent firm’s

Entry production region product

Modes factors factors factors

Minority JV (n = 11)

[beta] -0.1106 0.1089 -0.1642

S.E. 0.2421 0.2870 0.8165

Sig. .6478 .7044 .8406

Equal JV (n = 7)

[beta] 0.1099 0.1238 -0.1531

S.E. 0.2358 0.2840 0.8289

Sig. .6410 .6629 .8535

Majority JV (n = 21)

[beta] -0.0104 -0.0344 -0.1632

S.E. 0.2116 0.2668 0.7391

Sig. .9607 .8975 .8252

SV (n = 5) 0 0 0

Parent firm’s Parent firm’s

resource decision task

Entry commitment related

Modes factors factors

Minority JV

[beta] -0.5491 -0.8684

S.E. 0.3817 0.6406

Sig. .1502 .1752

Equal JV (n = 7)

[beta] -0.3731 -1.2128

S.E. 0.3915 0.6312

Sig. .3406 .0547 ([dagger])

Majority JV (n =21)

[beta] -0.2465 -1.0485

S.E. 0.3562 0.5953

Sig. .4889 .0782 ([dagger])

SV (n = 5) 0 0

([dagger]): p < .10; *: p < .05; **: p < .01; ***: p < .001.

A positive [beta] coefficient means an increased probability of the

specific type of JV relative to a SV.

A negative [beta] coefficient means an increased probability of a SV.

TABLE 2: MEANS AND STANDARD DEVIATION FOR SIGNIFICANT VARIABLES (ANOVA

ANALYSIS)

Sample Mean (Standard Deviation)

Mean

(Standard Minority-JV Equal-JV

Variables Deviation) (N=11) (N=7)

China Environmental Factors:

Government policies and 4.95 5.36 5.29

regulations (0.83) (0.67) (0.76)

Level of the Chinese 4.59 4.82 4.86

government to deal with (1.02) (0.60) (0.69)

Role of the Chinese 5.11 5.64 5.57

government in the economy (0.89) (0.50) (0.53)

The status of economic 3.86 4.55 4.29

co-operation between China and (1.00) (0.69) (0.76)

parent firm’s country/region

Chinese people’s way of life 4.09 4.55 4.43

(0.77) (0.52) (0.53)

Way of doing business in China 5.11 5.64 5.86

(0.95) (0.50) (0.38)

Availability of infrastructure 4.14 4.82 4.29

(1.11) (0.87) (0.95)

Quality of infrastructure 4.30 5.36 4.43

(1.09) (0.50) (0.98)

Geographic proximity distance 2.80 2.73 3.71

between China and your parent (0.79) (0.79) (0.76)

firm’s country/region

China Market Factors:

Availability of marketing 4.93 5.55 5.14

infrastructure (0.87) (0.52) (0.69)

Quality of distribution 4.52 5.18 4.43

infrastructure (1.00) (0.60) (0.98)

Required cost of marketing 4.39 4.73 4.00

effort (0.92) (0.79) (0.82)

Parents Firm’s Resource

Commitment Factors:

Production skills 4.14 3.45 4.00

(0.73) (0.52) (0.58)

Management capacity 4.25 3.73 4.14

(0.72) (0.79) (0.69)

Mean (Standard

Deviation)

Majority-JV SV

Variables (n=21) (n=5)

China Environmental Factors:

Government policies and 4.86 4.00

regulations (0.73) (1.00)

Level of the Chinese 4.86 2.60

government to deal with (0.73) (1.14)

Role of the Chinese 4.95 4.00

government in the economy (0.92) (0.71)

The status of economic 3.48 3.40

co-operation between China and (0.98) (1.14)

parent firm’s country/region

Chinese people’s way of life 3.71 4.20

(0.78) (0.84)

Way of doing business in China 4.76 4.40

(1.00) (0.89)

Availability of infrastructure 4.10 2.60

(1.00) (0.89)

Quality of infrastructure 4.05 2.80

(0.86) (0.84)

Geographic proximity distance 2.52 2.80

between China and your parent (0.60) (0.84)

firm’s country/region

China Market Factors:

Availability of marketing 4.76 4.00

infrastructure (0.83) (1.00)

Quality of distribution 4.48 3.40

infrastructure (0.93) (1.14)

Required cost of marketing 4.67 3.00

effort (0.80) (0.00)

Parents Firm’s Resource

Commitment Factors:

Production skills 4.38 4.80

(0.59) (0.84)

Management capacity 4.52 4.40

(0.60) (0.55)

TABLE 3: ANOVA RESULTS FOR SIGNIFICANT VARIABLES

Variables F (3,40) p-value [[eta].sup.2]

China Environmental Factors:

Government policies and 4.3584 .0096 0.25

regulations

Level of the Chinese 13.3970 .0000 0.50

government to deal with

Role of Chinese government in 6.4447 .0012 0.33

the economy

The status of economic co- 4.3312 .0098 0.25

operation between China and

parent firm’s country/region

Chinese people’s way of life 4.1713 .0116 0.24

Way of doing business in China 6.0678 .0017 0.31

Availability of infrastructure 6.3230 .0013 0.32

Quality of infrastructure 12.8899 .0000 0.49

Geographic proximity, distance 5.0966 .0044 0.28

between China & your parent

firm’s country/region

China Market Factors:

Availability of marketing 5.3584 .0034 0.29

infrastructure

Quality of distribution 3.2502 .0316 0.20

infrastructure

Required cost of marketing 5.3584 .0003 0.37

effort

Parents Firm’s Resource

Commitment Factors:

Production skills 8.0132 .0003 0.38

Management capacity 3.6413 .0206 0.21

Post-hoc Test (Significant Level)

Minority Minority Minority

vs. vs. vs.

Variables Equal JV Majority JV SV

China Environmental Factors:

Government policies and n.s. n.s. **

regulations

Level of the Chinese n.s. n.s. ***

government to deal with

Role of Chinese government in n.s. ([dagger]) **

the economy

The status of economic co- n.s. * n.s.

operation between China and

parent firm’s country/region

Chinese people’s way of life n.s. * n.s.

Way of doing business in China n.s. * *

Availability of infrastructure n.s. n.s. ***

Quality of infrastructure ([dagger]) *** ***

Geographic proximity, distance * n.s. n.s.

between China & your parent

firm’s country/region

China Market Factors:

Availability of marketing n.s. * **

infrastructure

Quality of distribution n.s. n.s. **

infrastructure

Required cost of marketing n.s. n.s. ***

effort

Parents Firm’s Resource

Commitment Factors:

Production skills n.s. ** **

Management capacity n.s. * n.s.

Post-hoc Test (Significant Level)

Equal JV Equal JV Majority JV

vs. vs. vs.

Variables Majority JV SV SV

China Environmental Factors:

Government policies and n.s. * n.s.

regulations

Level of the Chinese n.s. *** ***

government to deal with

Role of Chinese government in n.s. ** ([dagger])

the economy

The status of economic co- n.s. n.s. n.s.

operation between China and

parent firm’s country/region

Chinese people’s way of life n.s. n.s. n.s.

Way of doing business in China * * n.s.

Availability of infrastructure n.s. * *

Quality of infrastructure n.s. ** *

Geographic proximity, distance ** n.s. n.s.

between China & your parent

firm’s country/region

China Market Factors:

Availability of marketing n.s. ([dagger]) n.s.

infrastructure

Quality of distribution n.s. n.s. ([dagger])

infrastructure

Required cost of marketing n.s. ([dagger]) ***

effort

Parents Firm’s Resource

Commitment Factors:

Production skills n.s. n.s. n.s.

Management capacity n.s. n.s. n.s.

n.s.: not significant; ([dagger]): p < .10, *: p < 05; **: p < .01;

***: p < .001.

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Author Profile

Dr. JIANG Fuming earned his Ph.D. at The Australian Graduate School of Entrepreneurship, Swinburne. Currently he is a researcher, lecturer and course coordinator in international business in The School of Business and Information Management at The Australian National University, Australia.

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