Determinants of New Venture Performance: Empirical Evidence from Vietnam’s New Manufacturing Ventures. Nham Phong Tuan E-mail: [email protected] Position: Lecturer in Faculty of Business Administration, Vietnam Commercial University and PhD student in Graduate School for Development and Cooperation, Hiroshima University. 1-5-1 Kagamiyama, Higashi-Hiroshima, JAPAN 739-8529

Takahashi Yoshi E-mail: [email protected] Position: Associate Professor Graduate School for Development and Cooperation, Hiroshima University. 1-5-1 Kagamiyama, Higashi-Hiroshima, JAPAN 739-8529

Acknowledgments： The authors would like to thank Ms. Julie Sirois for proofreading. This research used dataset provided by the World Bank. All errors and omissions remain the responsibility of the authors.

Abstract This paper focuses on analyzing the topic of new venture performance in Vietnam. Specifically, it examines the factors determining the growth of new manufacturing ventures in Vietnam. We reviewed the comprehensive framework of new venture performance and applied it partly for Vietnam’s case. This study uses the sample of 312 new manufacturing ventures derived from secondary dataset of the World Bank. Our results indicate that international market expansion strategy through exporting, geographic location, financial resources, ownership structure of Limited and FDI Company are significant predictors. That significance differs by technological levels among industry sectors. In Vietnam, however, characteristics of owners/managers are not determinant.

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Determinants of New Venture Performance: Empirical Evidence from Vietnam’s New Manufacturing Ventures.

Abstract This paper focuses on analyzing the topic of new venture performance in Vietnam. Specifically, it examines the factors determining the growth of new manufacturing ventures in Vietnam. We reviewed the comprehensive framework of new venture performance and applied it partly for Vietnam’s case. This study uses the sample of 312 new manufacturing ventures derived from secondary dataset of the World Bank. Our results indicate that international market expansion strategy through exporting, geographic location, financial resources, ownership structure of Limited and FDI Company are significant predictors. That significance differs by technological levels among industry sectors. In Vietnam, however, characteristics of owners/managers are not determinant.

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Introduction Since Vietnam’s economic reform program—officially called the “doi moi”- was launched in 1986, the Vietnamese economy has increasingly developed and has experienced one of the biggest growth in the world. Over the past 20 years, people’s living standards in Vietnam have substantially improved and socio-economic achievement has also been really impressive, especially in terms of the presence of newly established firms. New ventures, mostly small and medium-sized enterprises (SMEs), have been a driving force for the development of Vietnam’s economy. New ventures in the manufacturing sector have proved their potential for development and have made the biggest contribution to the country’s GDP and employment. It has been estimated that in recent years, around 1.6 to 2 million new jobs were created by new ventures while the foreign invested sector and state-owned enterprises (SOEs) only created a relatively small share of them (Ba et al., 2006). Obviously, new manufacturing ventures play a crucial role in the national economy. It is not hard to understand why policy makers always issue preferential policies to develop this sector. However, in Vietnam’s case, there is still a lack of empirical research about new manufacturing ventures, especially researches about their characteristics, and the factors affecting their performance. Studies about new venture performance started in the 1980s, and afterwards a lot of these researches were implemented. They are still a hot topic nowadays (Gilbert et al., 2006). Reviewing previous studies showed us that researchers already suggested quite comprehensive models on new venture performance, and they also proposed direction for future researches. Based on these suggestions and the need for more empirical evidence, especially in Vietnam’s situation, the purpose of this study is to examine the determinants of new manufacturing venture performance in Vietnam. This paper uses data from the Productivity and Investment Climate Enterprise Survey implemented by the World Bank in 2005. The sample used for analysis in this study is the one of manufacturing new ventures in five regions of Vietnam. This article is organized as follows: the next section briefly reviews the past literature studying models of new venture performance and develops hypotheses. Following that, the third section presents the data and sample as well as the analytical framework, variables and their measurement. In the fourth section, analysis methods and model are reported. The fifth and sixth sections show the results, the related discussion and the conclusion, respectively. Literature review and hypothesis development New venture performance has attracted the interest of many scholars researching about enterprises since the 1980s (Gilbert et al., 2006). First of all, it is necessary to discuss the definition of what is called a new venture. After reviewing previous studies on new venture, Chrisman et al (1998: 6) said that A new venture is the end result of the process of creating and organizing a new business

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that develops, produces, and markets products or services to satisfy unmet market needs for the purposes of profit and growth (Gartner, 1985; Normann, 1977; Sandberg, 1986)… A venture is considered new if it has not yet reached a phase in its development where it could be considered a mature business… The length of time it takes for a new venture to mature will vary depending on its industry, resources, strategy, etc. It seems reasonable to assume that the earliest this might occur would be three to five years after its creation, and, more usually, not until the venture is eight to twelve years old (Biggadike, 1979; Kazanjian & Drazin, 1990)…

This article does not intend to discuss deeply on the definition of new ventures but rather to apply their ideas in order to reach appropriate researching observations. On the other hand, it should be noted that although most new ventures are considered small and medium-sized enterprises (SMEs) in terms of numbers of employees, they also have the possibility to develop to the larger scale of the so-called established firms. It means that by considering new ventures, we are focused on the process of development from their inception to their maturity, but SMEs still belong to a different sector than large firms. Therefore, there are many cases in which the scale of new ventures is larger than the one of SMEs, or others where the age of SMEs goes beyond what defines new ventures. Conceptual Framework In this section, the main models of new venture performance are reviewed to identify factors believed to explain why some new ventures outperform others. The primary models of new venture performance argue that success is based only on the biographical and psychological characteristics of entrepreneurs, which are their educational background, prior experience, need for achievement, beliefs and risk preferences (Sandberg, 1987). Unfortunately, most of the findings have not showed a strong relationship between them (Sandberg, 1987). Based on his own arguments, Sandberg (1987) proposes that new venture performance is a function not only of the characteristics of entrepreneurs, but also of industry structure and strategy. Sandberg’s (1987) model is considered a starting model of reviewing literature in many successive researches. In their 1998 research, Chrisman et al. argue that new venture formation is a special case of strategic management theory and thus, they extended Sandberg’s (1987) model to include the resources and the organizational structure, processes, and systems. Although that article is not an empirical study, it provides a more comprehensive direction for future research on new venture performance. One of the most recent researches on new venture performance was the one done by Brett Anitra Gilbert, Patricia P.McDougall and David B.Audretsch in 2006. This study tried to systematically review almost all researches previously done on new venture performance, starting with the Sandberg model (1987). After combining these studies, they concluded that the most important factors for new venture performance are the entrepreneur characteristics, resources, strategy, industry, and organizational structure and systems (Gilbert et al., 2006). In addition, in the process of reviewing recent researches, they added one predictor of new 42

venture performance, the geographic location. Perhaps their most important contribution has been to examine two key decision-makings related to new venture performance or growth: how and where new ventures perform or grow. They argue that the current literature on new venture performance has focused only on why new ventures grow but excluded these two decisions. They believe those decisions are important gaps in the literature that should be filled in to improve the knowledge on new venture performance (Gilbert et al., 2006). According to them, how new ventures grow is through internal or external means, and where they grow is on domestic or international markets. These three researches are considered emphasizing points in the general picture of research on new venture performance. Except for Sandberg’s (1987) research, the others were not empirical ones. In addition, in comparison with the research done by Chrisman et al (1998), the one of Gilbert et al (2006) is more comprehensive due to the updating with more recent researches. It leads us to say that it is not easy to implement comprehensive researches, and in fact, so far, there have not been such researches. Most of the previous empirical researches focused only on some specific aspects. The reasons for this might be related to the difficulty of collecting data. Moreover, Sandberg (1987) implied that future studies on new venture performance must either more carefully limit their domains or be built on contingency models of performance. This article tries to apply a comprehensive model of new venture performance as much as possible. However, it is not as ambitious as to refer to all aspects. More important, this is a primary and exploratory study of Vietnam’s case. Thus, it is more appropriate to focus on Vietnam’s features of socio-economic development nowadays. Specifically, this study emphasizes on one implication of Gilbert et al (2006) for future studies on new venture performance, which was that new ventures outperform in domestic or international markets. Besides, some predictors for explaining why new ventures outperform, such as: the geographic location, characteristics of owners/managers, financial resources, industry technological characteristics, and organizational structure and systems are considered. Previous Researches on Factors Affecting New Venture Performance and hypothesis development This article is based on the comprehensive model of new venture performance, which latest version is considered by Gilbert et al (2006). However, it focuses only on some appropriate predictors for Vietnam as the primary study of this topic. In the following section, Gilbert et al’s (2006) overview is used as a base for reviewing the most recent researches, and then for arguing the development of our hypotheses and formulating our own model of growth for testing data in Vietnam. Domestic or International Market In their research, Gilbert et al (2006) argue that one of shortcomings of the current literature on new venture performance is that it omits the key decision of where new ventures outperform (i.e., domestically or internationally). Whether outperforming domestically or 43

internationally, a firm can follow one of two marketing expansion strategies including market penetration and market development strategies (Gilbert et al., 2006). No matter what expansion strategies are used and in which markets (domestic or international), they can affect the performance of new ventures (Brouthers et al., 2004; Gilbert et al, 2006). However, Shrader (1996) found that for sales performance, international strategies outperformed the domestic ones. Further investigation also found that the international ones generated twice more sales per employee than the domestic ones (Gilbert et al., 2006). Moreover, in spite of a positive relationship between the international ones and sales growth, additional examination is needed to validate these results (Gilbert et al., 2006). On the other hand, Gilbert et al (2006) share the view of Brouthers et al (2004) that the mode of entry on international markets may influence the performance of new venture. For example, the international expansion strategy by exporting can increase sales rather than the number of employees, whereas modes of foreign direct investment or joint venture impact on the number of employees before the sales or market share (Gilbert et al., 2006). Therefore, there is much to be discussed about where new ventures outperform. H1: Export strategy is significantly and positively related to new venture performance. Financial resources Financial resources, expressed by financial capital, are one of the determinants for the success of firms (Cooper et al., 1994; Lee et al., 2001; Gilbert et al., 2006). Financial capital is important because it allows entrepreneurs to implement strategic objectives or meet the financing needs for the performance of new ventures. The amount of capital also has a positive effect on venture survival (Cooper et al., 1994). In fact, for new ventures, even though internal funds or the owner’s capital is essential to start, it is not really adequate for competing and sustaining the subsequent period’s growth. That is why it is necessary for new ventures to mobilize external capital from both formal and informal sources. Obviously, external sources of finance such as banks and venture capitalists have a great impact on new venture performance (Lee et al., 2001; Gilbert et al., 2006). However, accessing external capital is always a problem for new ventures because of their lack of reputation and liability. Therefore, an empirical examination of Vietnam’s case should be implemented to pave a clearer way for supportive policies. As for the capital ownership of a firm, keeping balance between internal funds and external financing is important. Otherwise, over a certain amount of external capital poses a big risk for business activities. H2: Financial resources are significantly and positively related to new venture performance, but this effect tends to diminish according to the amount of capital. Geographic location 44

According to the resource-based view, geographic location is among the much intangible resources (Chrisman et al., 1998). However, this variable is becoming more important if known as an industrial zone, agglomeration or cluster, especially in growing economies and in a context of economic globalization. Definitions of industrial zone or cluster range from the very broad to the extremely narrow. This article takes the approach of industrial zone, which may be seen as a subjective concentration of firms located within a limited geographic area. Lechner et al. (2003) found that a new venture’s geographic location has a significant impact on its survival. Location in an industrial zone or industrial district or cluster has strong implications when the ability to acquire resources in differing locations is taken into account (Gilbert et al., 2006). For example, financial and human resources can be accessed more easily for a firm located in cluster locations like Silicon Valley (Saxenian, 1990; Porter, 1995). Cluster locations can provide a better source of capital and quality workers, spillover of technology, reducing transaction costs and thus enabling new ventures to pursue better outcomes. H3: Firms located in industrial zones are significantly and positively related to new venture performance. Organizational structure and systems In the strategic management theory, the structure-conduct-performance framework is among the most well-known (Hoskisson et al., 1999). This framework implies that an organization's structure and systems are the primary means by which it implements its strategy. It engages in many operational processes such as selecting and building a structure to divide work; coordinating and integrating functions; facilitating flows of information; managing human resources and controlling behaviors of organizational members (Galbraith et al., 1986; Chrisman et al., 1998). According to the review of Chrisman et al. (1998), empirical research has indicated that the organizational structure and systems of a new venture are associated with its performance (Eisenhardt, 1989; Duchesneau et al., 1990, and many more). One of the organizational structure and system variables that research and theory suggest as most significant is the ownership structure (Chrisman et al., 1998). Different ownership structure leads to different organizational structure and systems. For instance, the impact of functional specialization and decision making structure investigated by Kazanjian et al. (1990) is significant for the growth of new ventures. Barringer et al (2005) indicated that training, financial incentives and stock options are common features in outperforming new ventures (Gilbert et al., 2006). Moreover, ownership structure can be expressed by legal statuses of new venture. In Vietnam’s case, some main legal forms are: Limited Liability Company, Joint Stock Company, Private Company and State-Owned Enterprises. Among these legal forms, the Limited Liability seems to be a popular choice because it liberates owners from some types of liability related to business operation (Davidsson et al., 2002). It 45

has often been investigated against the other forms in empirical studies. It is generally said that the Limited Liability Company type outperforms the others (Storey, 1994; Davidsson et al., 2002). H4: New ventures engaged in the legal form of Limited Liability and FDI Company outperform new ventures with other legal forms. Characteristics of owners/managers Most of the research on new venture performance in the early period focused only on characteristics of owners/managers or entrepreneurs such as: education, experience, need for achievement, risk preferences, etc. Although researchers were not able to show a strong relationship between those characteristics and new venture performance and thus Sandberg (1987) suggested a new model by adding two new variables (Industry Structure and Strategy), characteristics of owner/managers could explain more or less performance of new ventures. Education and experience of owner/managers are important because they help entrepreneurs exploit relevant information and provide competencies to make strategic decisions of deploying resources for their ventures (Mullins, 1996) and, thus they influence the performance of new ventures. It seems that although the characteristics of owner/managers have an indirect rather than a direct effect on the performance of new ventures because they influence firstly the quality of decisions and then outcomes, most researchers examine these characteristics directly to the sales growth of the firms (Gilbert et al., 2006). More recent researches by Eisenhardt et al. (1990), Box et al. (1993), Cooper et al. (1994), and Baum et al. (2001), show that education and experience have significant and direct effects on the sales and employment growth of new firms (Gilbert et al., 2006). Obviously, characteristics of entrepreneurs, especially education and experience, have well-established effect on new venture performance. H5: Higher educational background of owner/manager has a significant and positive impact on venture performance. H6: Prior sector experience of owner/manager has a significant and positive effect on venture performance. Industry Technological Characteristics Industry structure or context is one of the first factors entrepreneurs have to consider not only for their firms start-up but also their operation in the following periods. Entrepreneurs base the strategic decisions for their firms on the industry context. Industry characteristics such as: the stage of industry evolution, barriers to entry and mobility, nature of rivalry, power of buyers and suppliers, nature of buyer needs, degree of industry heterogeneity and various industry sectors, provide both opportunities and challenges that affect the probability 46

of survival and success of new ventures (Porter, 1980; Chrisman et al., 1998). This paper focuses on different industry sectors classified by technological levels. Industry sectors with various technological levels have different impact on new venture performance. In fact, in many empirical researches, the sample of new ventures is not only constituted from new manufacturing ventures in general but also from specific new ventures reflecting technological level such as the semiconductor ventures (Eisenhardt et al., 1990), technology-based ventures (Kazanjian, 1990; Lee et al., 2001), software ventures (Zahra et al., 1999), high tech and knowledge-intensive ventures (Bollingtoft et al., 2003), and technology-intensive ventures (McGee et al., 1994). Among these specific samples, determinants that affect performance of new ventures are different or if similar, contribution of those factors is not consistent. These prove that the performance of new ventures might be different among various industry sectors according to their technological levels, and these different samples should not be predicted by same factors. Therefore, it is necessary to examine the performance of new ventures in different industry sectors, and determinants for each specific industry sample. H7a: Performance of new ventures is different among industry sectors with various technological levels. H7b: Contribution of determinants for each specific industry sample by technological levels is different. Methodology Data and Sample This paper uses data from the Productivity and Investment Climate Enterprise Survey1 implemented by the World Bank in 2005. This survey was conducted in five main regions2 of Vietnam. The total number of observations was 1150 enterprises. All enterprises belonged to the manufacturing sector with many different industries. The sample used to analyze in this study are the manufacturing new ventures operating in those five regions of Vietnam. As showed in the previous section, there is not a single definition for new ventures. Most previous researches about new ventures were based on the length of time since the firms were established. The length of time often chosen by authors is around 10 years (Box et al., 1993; Chandler et al., 1994b; Zahra et al., 1999; Forbes, 2005). Based on this idea, the sample used in this study is firms that have operated for around ten consecutive years from 1995 to 2005. According to that identification, there were totally 445 new manufacturing ventures. However, to be suitable for this research, we removed cases that began operating in 2002, 2003, 2004, or that had missing data and biased values. Therefore, only 312 new manufacturing ventures are used as the sample for analysis in this paper. Research Variables 47

From the conceptual framework and hypothesis development of the previous section, it can be seen that this empirical research contains some specific variables as follows: Dependent Variable The performance of a new venture can be measured by criteria such as its survival and success (Chrisman et al., 1998). Survival for a venture means that its operations can last over several years, and success is when it creates value for its customers in a sustainable and economically efficient manner in those initial years (Chrisman et al., 1998). Success can be measured with indicators such as: profitability (ROA, ROE and ROI), growth rate of sales, employees and market share. Whereas profitability measures are not used because they are not appropriate for new ventures (Chandler et al., 1994a), sales growth is the most frequently used indicator (Weinzimmer et al., 1998). Therefore, this study uses growth of sales as an indicator of new venture performance. Growth rate of sales is calculated by the mean values of sales growth rate from 2002 to 2004. Independent Variables Market Expansion Strategy: This study focuses on international market expansion strategy through exporting. It is measured by the percentage of export sales out of the total sales in 2004. Ownership Structure: This variable is expressed by the legal forms of Limited Liability and FDI Company, One member Ltd Company, Joint Stock Company, Sole proprietorship, and SOEs. Its measurement is a dummy variable with Limited Liability and FDI company coded 1 and otherwise 0. Geographic Location: Industrial zone is its proxy which is measured by 1 if firms are located in an industrial zone and 0 if otherwise. Industry sector: There are many methods to classify industry sectors. However, this study focuses on the technological levels of products identified by Lall (2000). According to him, there are five technological levels of products including: Primary products, Resource-based, Low-technology, Medium-technology and High-technology manufactures. To be fit with our data, only four levels are used –we excluded primary products. Based on these four levels, the numbers of firms are grouped into three smaller samples – Resource-based, Low-technology, and Medium and High-technology manufactures. Therefore, this variable is coded by ordinal numbers 1, 2 and 3 corresponding to three technological levels. Financial Resources: This predictor is measured by the percentage of external capital in comparison with internal funds in the total capital for its 2004 business operation. Educational Background: This variable is measured by ordinal numbers from 1 to 6 corresponding to the level of education of the owner/manager from the lowest through the highest level: Did not complete high school; High school; Vocational training; Some College or University training; Graduate degree (BA, BSc etc.), and Post graduate degree (PhD, Masters). Prior Sector Experience: This variable is measured by years of experience working in this 48

sector before running the firm. In this sample, prior sector experience ranges from 0 to 38 years. Control Variables Firm size: the size of firm used in this research is measured by average numbers of employees in three years 2002, 2003 and 2004. However, to avoid bias of data, firms with numbers of employees in the range of more than 10 and less than 1000 people are accepted. In fact, the numbers of SMEs (10-300 employees) are a majority in the sample. Firm age: This variable is measured by using scales from the established year to the year 2005. As definition of new ventures in this study, firms were established at the earliest in year 1995. Therefore, the age of firms in this sample is from 4 to 10 years. Analyses The Multiple Regression analysis is used as the main quantitative analysis method. The relationship between independent and dependent variables is modeled in the following equation: Yi = a + bXi + e Where Y represents the growth rate of sales (GrS) in ith SMEs, Xi represents the control and independent variables such as firm size (FS), firm age (FA), export strategy (EX), financial resource (FR), financial resource square (FRS), geographic location (GL), ownership structure (OS), educational background (EB), prior sector experience (PSE), industry sector (IS), a is intercept, and e is error term. The details of the relationship between variables are illustrated in the equations below: GrS = a + b1FS + b2FA + b3EX + b4FR + b5FRS + b6GL + b7OS + b8EB + b9PSE + b10IS + e Results and Discussion Table 1: Descriptive Statistics Variables

Mean.

SD.

(1)LogFS 1.91 0.48 (2)LogFA 0.77 0.13 (3)EX 29.86 41.02 (4)FR 65.78 36.85 (5)FRS 5681.54 4029 (6)GL 0.19 0.39 (7)OS 0.56 0.5 (8)EB 4.43 1.27 (9)PSE 10.15 7.62 (10)IS 1.87 0.73 (11)GrS 26.2 36.44

1 1 0.17** 0.38** 0.2 0.02 0.18** 0.08 0.38** 0.14* -0.09 0.03

2

3

4

5

1 0.97** -0.02 -0.02 -0.02 0.01 -0.07 0.12*

1 -0.01 -0.02 -0.03 0.01 -0.07 0.1

6

7

8

9

10

11

1 0.001 -0.09 -0.1 -0.01 0.03 0.16** 0.05 0.08 -0.14*

1 0.01 0.04 0.06 0.12* -0.01 0.1 -0.08 0.21*

*, ** and statistically significant at 5% and 1% respectively 49

1 0.01 0.17** 0.01 0.03 0.2**

1 0.11 1 -0.02 -0.03 1 0.25** 0.14* 0.07 1 0.15** -0.02 0.07 -0.01

1

Table 2 Results of multiple regression analysis Explanatory Variables Constant LogFS LogFA EX FR FRS GL OS EB PSE IS R square Adjusted R square F statistics Durbin-Watson N(firms)

Growth rate of sales Model 1 40.986*** -8.600* -34.400** 0.218*** 0.501** -0.004* 18.628*** 9.691** -0.062 0.283 -1.064 0.151 0.121 5.176 2.129 312

Model 2 Model 3 Model 4 25.957 37.443* 19.454 -1.933 -17.397** -6.146 -23.633 -18.99 -69.816** 0.197** 0.315*** 0.072 0.68 0.321 1.069* -0.004 -0.002 -0.01* 25.641*** 18.908** 6.082 18.665** 3.588 10.565 -4.617 1.95 8.774* 0.314 0.171 0.407 0.235 0.161 3.148 1.941 105

0.187 0.13 3.289 1.869 143

0.158 0.012 1.09 2.291 64

*, ** and *** statistically significant at 10%, 5% and 1% respectively Table 1 provides descriptive statistics including product moment correlation (Pearson), mean, and standard deviations. Correlations among independent variables are not significant or very low except for the correlation coefficient between the variables FR and FRS that is high, certainly because FRS is square of FR. Generally speaking, this early analysis indicates that there are no serious problems with multicollinearity that would violate assumptions for the general linear model. Table 2 reports the results of various regression models explaining sales growth. Four models are estimated. Excepting for model 1, three remaining models are the same with each other about predictors but different about samples. Model 1 is estimated on the whole sample of 312 firms. From model 2 to model 4, the whole sample is divided into smaller groups by technological levels of products corresponding to industry sectors. Model 2 includes the sample of firms belonging to resource-based manufactures. The sample of Model 3 is low technology. Model 4 corresponds to the sample of medium and high technology manufactures. Through regression coefficient and significant level of each independent variable, whereas most hypotheses in this study will be examined by emphasizing model 1, model 2 to model 4 proves the hypothesis 7b. From this table, firstly, in model 1, it can be found that the variable Export Strategy (EX) has a positive impact on sales growth at a statistical significant level of 1%. Similarly, 50

variables such as Financial Resource (FR), Geographic Location (GL) and Ownership Structure (OS) have a positive effect on sales growth at a significant statistical level of 5%, 1% and 5%, respectively. On the other hand, variables including Firm size (FS), Firm age (FA) and Financial Resource Square (FRS) have a negative influence on sales growth at significant statistical levels of 10%, 5% and 10%, respectively. The three variables Educational Background (EB), Prior Sector Experience (PSE) and Industry Sector (IS) do not have a statistically significant effect on sales growth. Therefore, these findings support hypotheses H1, H2, H3, H4 and H7b and reject hypotheses H5, H6 and H7a. Hypothesis H1 is supported; it means that the more new manufacturing ventures are engaged in international market expansion through export strategy, the highest growth rate those ventures experience. This finding adds more empirical evidence for the significance of export strategies. In reality, in Vietnam’s case, export stimulation is always considered one of the preferential policies of the government. Thus, firms engaging in export activities usually receive support from those policies. To some extent, this finding proves the effectiveness of those policies in Vietnam. Hypothesis H2 implies that the bigger the proportion of external capital in capital structures for business operation, the higher the sales growth. However, to a certain amount of external capital, the performance is diminished because of the risky feature of external capital. On the one hand, this finding indicates that the external capital for business operation in new ventures is significant for their performance. Those who can access more external funds perform better. Not surprisingly, in order to promote entrepreneurs, financial policies should be supportive, and not only in Vietnam’s case. On the other hand, this result also confirms one feature of external capital, which is that firms will face risks when borrowing externally capital over a certain threshold. It leads firms to carefully consider their amount of external capital and its spending. Hypothesis H3 means that firms located in industrial zones outperform firms who are not. Perhaps we do not need to explain more about the advantages of this geographic location. Actually, in Vietnam’s case, the government’s current policies of industrial promotion are supporting the development of industrial zones or industrial districts or clusters. Hypothesis H4 indicates that organizational structure and system is one of the important variables explaining the performance of new ventures. Obviously, various legal statuses imply different organizational structure and system. This finding emphasizes that the legal forms of Limited Liability and FDI Company outperform the others, such as the One member Ltd Company, Joint Stock Company, Sole proprietorship, and SOEs. It can be said that this form has outstanding features attracting new manufacturing ventures. Both of hypotheses H5 and H6 are rejected. This result is quite surprising for common sense, although these two variables do not have a strong impact in traditional academic researches either (Sandberg, 1987). This can be explained by the fact that most 51

owner/managers in the sample have a relatively high education and are still young. In many cases, experience is not meaningful because some older owner/managers came from SOEs: their experience could not be applied in the new business environment and they had difficulty in unlearning. Vietnamese firms operate in a rapidly evolving and unstable environment. Moreover, the kind of things these owner/managers had learned in universities and training courses clearly have been of little use to them in real business. Therefore, education and experience of owner/manager are not determinants for the performance of new ventures, but sometimes, sudden opportunities in unstable business environments can determine success. For the control variables Firm Size (FS) and Firm Age (FA), although these variables are not focused, they may be factors affecting the performance of new ventures. Our findings show that those two variables have a negative influence on new venture performance at a statistically significant level of 10% and 5%, respectively. This result is understandable, because most firms in our sample are SMEs. A majority of empirical researches agree that for the SMEs sector, the smaller the size of a business, the greater their growth; and younger businesses grow more rapidly than older ones. As it is indicated that hypothesis H7a is rejected. It means that there is no statistically significant difference among industry sectors in terms of sales growth. From model 2 to model 4, it can be seen how different the models are through checking the significance of regression coefficients and R squares and thus, hypothesis H7b is tested. Generally speaking, the impact of predictors on sales growth of these three models is different. For comparing R squares of the three models, model 2 with the sample of resource-based manufacturing firms has the highest level (0.235), a lower one belongs to model 3 representing the sample of low-technology manufacturing firms, and the lowest one is model 4, the sample of medium and high- technology firms. Hence, it seems that the sample of resource-based new manufacturing ventures is the most appropriate for the predictors in Vietnam’s case. However, these predictors might be not good indicators for the case of medium and high-technology new ventures. In addition, looking at the regression coefficient of predictors and its significant level in three models, except for the control variables that are quite consistent among models, the main explanatory variables vary more or less. For example, the variables Export Strategy and Geographic Location in model 2 are similar to model 3 but not significant for model 4. Financial Resources and its square are not important predictors in model 2 and 3 but significant for model 4 at a level of 10%. Interestingly, Educational Background has a significant and positive influence only in model 4. Obviously, hypothesis H7b is supported partly because among various technological levels of industry sectors is the determinants for performance of new ventures different, even though it is not reported whether the difference is statistically significant or not. Conclusion This paper has focused on studying the determinants affecting the new manufacturing ventures’ performance in Vietnam. In other words, this research has investigated the 52

relationship between some independent variables (export strategy, financial resources, geographic location, organizational structure and system, educational background and prior sector experience of owner/managers, and industry sector) and one dependent variable (sales growth). The determinants for performance of new ventures among different industry sectors classified by technological level of products were also examined. Based on the theoretical and empirical discussions found in the literature, the model of new venture performance used in this study applied partly the framework suggested by Gilbert et al (2006). After analyzing the data sample, it can be concluded that the more new manufacturing ventures engage in international market expansion through export strategy, the higher growth rate they will experience. The bigger their portion of external capital for business operation is, the higher their sales growth. However, to a certain amount, the performance is diminished because of the risky features of external capital. Moreover, firms located in industrial zones outperform firms who are not. In terms of organizational structure and system, the legal forms of Limited Liability and FDI Company outperform others such as the One member Ltd Company, Joint Stock Company, Sole proprietorship, and SOEs. In addition, education and experience of owner/managers, and industry sectors are not determinants for new manufacturing ventures in Vietnam’s case. About control variables including firm size and firm age, similar to the findings obtained in most of the theoretical and empirical literature on SMEs, smaller size businesses have greater growth rate, and younger businesses grow more rapidly than older ones. Finally, there is evidence that the determinants for performance of new ventures are different among industry sectors classified by the technological levels of their products. Based on the empirical findings and some reliable information, this research has some implications for both the new manufacturing venture and the government sectors. For the new venture sector, firstly, entrepreneurs should implement the strategy of international market expansion through export. Export activities are supported by government policies. In order to export successfully, entrepreneurs should improve the ability of their new ventures against competitors. Secondly, resources are always important for survival and success. Owners/managers should make full use of the advantages of external capitals that are sometimes supported by credit programs of organizations. However, they also need to balance capital sources in their capital structure to reduce risks. Decision to locate their firms is significant for the accessibility to resources and the spillover of useful information. The operational mechanism or organizational structure chosen by entrepreneurs play an important role for internal resources. The government should play a certain role in creating a favorable environment for new ventures. The government should continue to give preferential policies for approaching external credits, and to attract more foreign direct investment into industrial zones. Gradually, foreign elements will create positive effects for the local business community such as technology transfer, management skills and useful information, and this will indirectly attract 53

more foreign investment. Like all other researches, this paper also has some limitations. The data used in this study has some weaknesses. The data comes from a World Bank survey. Some important variables in theoretical meaning could not be included in this model or some proxies may not really be good indicators. Moreover, the number of new ventures in the analysis sample is low, especially for the sample of medium and high-technology. This might be one of the reasons why model 4 is weak in its explanatory power. Finally, further studies should be implemented. These should focus on the internal characteristics and resources of new ventures, and the question of how new ventures perform (internal growth or external growth), an aspect recognized by Gilbert et al (2006), but that was not examined in this paper. Also, this research only indicates the significance of export strategies but does not tell us what contributes to export performance. Finally, this study used a model that captures only the direct effects on growth. Future studies should also consider other effects such as the mediated or moderated effects. These effects may show better results. Notes (1) The general purpose of the survey is to understand the investment climate in Vietnam and how it affects business performance, with the objective of helping improve it. (2) Red river delta, Mekong river delta, Northern central, South East and Southern central coastal. References Ba, L.X., Hao, T.K., & Thang, N.H. 2006. Vietnam’s SMEs in condition of international economic integration. National Politic publishing house: Hanoi. Baum, J. R., Locke, E. A., & Smith, K. G. 2001. A multidimensional model of venture growth. Academy of Management Journal, 44: 292-303. Barringer, B. R., Jones, F. F., & Neubaum, D. O. 2005. A quantitative content analysis of the characteristics of rapidgrowth firms and their founders. Journal of Business Venturing, 20: 663-687. Bollingtoft, A., Ulhoi, J. P., Madsen, H., & Neergaard, H. 2003. The effect of financial factors on the performance of new venture companies in high tech and knowledge-intensive industries: An empirical study in Denmark. International Journal of Management, 20: 535-547. Box, T. M., White, M. A., & Barr, S. H. 1993. A contingency model of new manufacturing performance. Entrepreneurship Theory & Practice, 18(2): 31-45. Brouthers, K. D., & Nakos, G. 2004. SME entry mode choice and performance: A transaction cost perspective. Entrepreneurship Theory & Practice, 28: 229-247. Chandler, G. N., & Hanks, S. H. 1994a. Founder competence, the environment and venture performance. Entrepreneurship Theory & Practice, 18(3): 77-89. Chandler, G. N., & Hanks, S. H. 1994b. Market attractiveness, resource-based capabilities, venture strategies, and venture performance. Journal of Business Venturing, 9: 331-349. Chrisman, J. J., Bauerschmidt, A., & Hofer, C. W. 1998. The determinants of new venture performance: An extended model. Entrepreneurship Theory & Practice, 23: 5-29. Cooper, A. C., Gimeno-Gascon, F. J., & Woo, C. Y. 1994. Initial human and financial capital 54

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