So sánh hoạt động huy động vốn đầu tư của các doanh nghiệp khởi nghiệp sáng tạo Việt Nam

Nội dung text: So sánh hoạt động huy động vốn đầu tư của các doanh nghiệp khởi nghiệp sáng tạo Việt Nam

1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 A COMPARATIVE ANALYSIS OF STARTUPS FINANCING IN VIETNAM SO SÁNH HOẠT ĐỘNG HUY ĐỘNG VỐN ĐẦU TƯ CỦA CÁC DOANH NGHIỆP KHỞI NGHIỆP SÁNG TẠO VIỆT NAM Nguyen Thi Hanh, Le Thai Phong Foreign Trade University hanhnt@ftu.edu.vn ABSTRACT The purpose of this paper is to compare the ability and efficiency of start-ups financing in Vietnam during 2010 - 2018. Probit regression is employed to clarify the differences of fundraising ability among some sectors. In addition, liner regression is also applied for investigate the efficiency of start-ups financing. The finding shows that start- ups in financial technology and e-commerce have advantages in raising capital. Furthermore, start-ups in the service technology dominate the efficiency of raising money. In addition, the study also shows that the older of start-ups age, the higher ability and efficiency of capital mobilization. The paper attributes valuable results to both academic and practical field. Entrepreneurs can seize oppotunity to be success in the new venture. Paper can be better if it takes a deep research in some characteristics of seperate industries and comparative. Keywords: Start-up finance, economics sectors, technology-based company. TÓM TẮT Bài nghiên cứu so sánh khả năng và hiệu quả huy động vốn đầu tư của các doanh nghiệp khởi nghiệp sáng tạo ở Việt Nam trong giai đoạn 2010 - 2018. Nghiên cứu sử dụng mô hình hồi quy biến nhị phân Probit để kiểm chứng khả năng hoạt động huy động trong các ngành khác nhau, tiếp theo sử dụng phương trình hồi quy tuyến tính để xem xét sự khác biệt của hiệu quả huy động vốn trong những ngành đó. Kết quả hồi quy cho thấy các doanh nghiệp thuộc ngành công nghệ tài chính và thương mại điện tử có lợi thế trong việc huy động vốn đầu tư. Bên cạnh đó, tuổi của doanh nghiệp khởi nghiệp cũng có tác động cùng chiều với hiệu quả huy động vốn. Nghiên cứu đã đóng góp một phần vào lý thuyết và thực tiễn của hoạt động huy động vốn của doanh nghiệp khởi nghiệp sáng tạo, vốn vẫn còn mới mẻ ở Việt Nam. Tuy nhiên bài nghiên cứu sẽ tốt hơn nếu có thêm các nghiên cứu sâu hơn từng lĩnh vực, đây cũng sẽ là hướng đi tiếp theo của nghiên cứu. Từ khóa: Huy động vốn đầu tư khởi nghiệp sáng tạo, khởi nghiệp sáng tạo, doanh nghiệp công nghệ. 1. Introduction Entrepreneurial activity fosters the innovation and technological change of a nation (Schumpeter, 1943). It is widely acknowledged the fact that places with high numbers of enterprises usually have high economic growth. This is because starting a business does not only create value for the economy but also create many job opportunities, thereby improving the quality of life of people. Shane (1995) demonstrates entrepreneurship is a key for the economic growth by investigating contribution of entrepreneurial firms to the US economic growth in the period 1947-1990. Moreover, new ventures are responsible for job creation (Vesper, 1996). Many studies (Stangler and Kedrosky, 2010; Kane, 2010) show that startups are accountable for almost all the new jobs created in the USA (about 63 percent). A research by Haltiwanger et al. (2013) on the US economy in the period 1992-2005 confirms that existing firms are job destroyers, losing one million jobs combined per year. By contrast, in their first year, new firms add an average of three million jobs. During recessionary years, job creation at startups remains stable. For all these reasons, entrepreneurship has attracted the attention of scholars since many decades and startups are becoming a growing area of interest. The success of start-ups has an impact on the economy, so that governments in developed and developing countries have adopted a variety of supportive policies and efforts, creating a favourable business environment to promote startups growth. 139
2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 For innovative startups, investment capital is very important, especially in the early stages so that businesses can maintain and realize their ideas. But a large percentage of innovative startups fail because of the lack of capital to implement their strategies and programs. Therefore, creating conditions for these businesses to have easy access to business capital is essential, but it is important to need help from the government to create a favorable environment to help businesses. creative start-up becoming more and more successful. Currently, the Ministry of Planning and Investment has a National Startup Support Fund with a capital of up to VND 2,000 billion, and Ho Chi Minh City has also developed a capital support policy for startups in the area, with the capital the investment for each project is up to VND 2 billion. However, the number of creative startups accessing this capital is very limited. The reason is that the policies supporting the start-up projects are still difficult for businesses to access capital, for example such as industry limitations, and the main cause is the human capital of the business owner. From the research on the factors affecting the capital raising activities of startups, we can see that the macro factors related to the industry environment are also important factors. For some businesses, the macroeconomic and sectoral context can affect profits more than the relative outcome of firms within the sector. Besides, the industry's profit has an impact on the ability and efficiency of raising capital of businesses, in detailed businesses need to pay attention to the macro economics and industry. This paper focuses on startups, which are fast growing, small, new and dynamic with annual growth rates ranging from 20 to 25 percent per year. The growth of the company may be due to the general growth of the industry or increase in market share also. Our analysis aims to figure out the diferences between industry in ability and efficiency of mobilization of Start-ups in Vietnam. This study contributes to the entrepreneurship literature specify in startup financing and provide important implications for researchers and practitioners who are more and more interested in startup companies in general. The research consists of five parts, in addition to the introduction section, the second part is the theoretical basis and research hypotheses. Next is the research data and methodology. The research results presents the results obtained from descriptive statistics and model regression. Finally, we provide conclusion and limitations of the study. 2. Literature review 2.1. Startup financing Entrepreneurship is a very complex category that involves many activities, such as identifying and evaluating opportunities and motives; search and allocate resources; corporate governance; fundraising. As pointed out by Clarysse et al. (2011), the growth paths of young technology-based firms result from structuring resource portfolios. Resources embrace human, technology, and financial resources. More specifically, this entrepreneurial model is usually associated to a need for capital exceeding the founders’ ability to self-fund and the company’s capability to self-sustain. Consequently, new ventures (also referred as “startups” or “young and new technology-based companies/NTBF”) in the early stages base their development on the resources collected through external financing, which comes from investors specialized on equity (seed and venture capital, as well as business angels, incubators, accelerators, recently also crowdfunding). Equity capital acquisition is one of the most critical factors in the growth path of a startup/new venture (Hustedde and Pulver, 1992; Colombo and Grilli, 2010; Colombo et al., 2010). The lack of adequate funds hinders firms’ growth and even threatens survival because it is strong correlated to resources acquisition (Carpenter and Petersen, 2002). Therefore, it is critical to understand the variables affecting the ability of new ventures – specifically in the early-stage phase – to access to financial resources. In additionaly, only a few studies have focused on the influence of human capital and firm’s characteristics on fund raising. Cressy (1996) suggests that human capital determines the ability of a company to access to financial resources, while others affirm that capital raised by a startup is positively related to the entrepreneurs’ level of education 140
3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 (Bates, 1990). By contrast, Storey and Wynarczyk, 1996 find that company-specific factors also have a great explanatory power as fund raising is involved. While the importance of equity capital on future new venture performance has been deeply investigated, access to equity capital for start-ups at an early stage and the existing linkages with human capital and firms’ characteristics still remain an open research problem. In particular, the study of factors affecting the successful fundraising of startups is quite new. However, research in the world often focuses on developed country contexts, where business environment is more advanced, and probably completely different from emergent contexts, such as in Vietnam. The research in Vietnam is very new, and it focuses mainly on the first issue (studying the factors that influence the entrepreneurial intention of the business). In addition, studies on the economic and environmental conditions of the industry, as well as factors on the type of business, also affect the performance of the business. Research by Khandwalla (1976) and Utterback (1996) shows that information technology enterprises are more likely to raise capital, so that the skills of human capital in information technology. The information of the business owner have a positive impact on the capital raising efficiency of the business. It is assumed that the impact of human capital on the capital mobilization results of innovative start-ups in high-tech industries will be greater than in low-tech industries. The year of establishment of an enterprise is also of interest to entrepreneurial researchers, according to Davidsson and Honig (2003), the age of the business is a key factor in assessing the capacity of human capital. Owners of young businesses are often more active than those of older businesses (Aldrich and Wiedenmayer, 1993; Stinchcombe, 1965). It is assumed that the impact of human capital on young firms on start-up capital mobilization will be greater than that of large firms. The first study in Vietnam by Tran Thi Thanh Huyen (2015), "Capital mobilization activities for startups: Current situation and solutions", highlighted the current situation of capital raising activities of start-up businesses. According to Nguyen Thi Hanh et al (2016), capital mobilization activities of Vietnamese start-ups exist in many forms and have not been clearly recognized by businesses and investors. There is an information asymmetry phenomenon, which leads to many difficulties in accessing investment capital of creative startups. According to Le Thai Phong et al (2018), factors affecting enterprises' capital mobilization activities come from the characteristics of the founders, enterprises and environmental and institutional factors. Researches on capital raising activities of innovative startups in Vietnam are still in the early stage. In these studies, most of the business or economic sectors are considered as an element of the observed variable and have not been studied in depth and analyzed in detail the specific characteristics of industries, especially for Creative start-up businesses. This study will analyze how to segment the industry for innovative startups and explore its impact on the ability and efficiency of raising capital. 2.2. Economic industrial classification Industry is a group of companies that provide similar products or services. These companies often have similar production processes, organizational behaviors, sales behaviors and markets. Industries are often categorized in a variety of ways, at the top level of the industry are often categorized into three groups: the basic industries (mining, agriculture), the manufacturing and the service sectors. The criteria for sub-sectors are often based on product functions and similar markets. For example, classification based on products such as construction, chemicals, petroleum, automotive, electronics, electricity, software, fisheries, textiles, etc. The market-based classification has Global Industry Classification Standard and Industry Classification Standard, which are commonly used for financial markets. There are also classification systems that apply this classification method: International Standard Industrial Classification of all economic activities of the United Nations, Standard Industrial Classification of the United States, and Vietnam System Industrial Classification (VSIC) in 2007. 141
4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 VSIC is divided into five levels with the following levels: level 1 consists of 21 sectors coded by the alphabet, level 2 consists of 88 industries formed by each corresponding level 1 industry and encoded with two digits From 01 to 99, level 3 consists of 242 sectors formed by each corresponding level 2 branch and encoded in three digits from 011 to 990, level 4 includes 437 branches formed by each corresponding level 3 branch and is encoded by four digits from 0111 to 9900, and a level 5 industry consisting of 642 sectors formed by each corresponding level 4 industry and encoded with five digits from 01110 to 99000. The economic sector in VSIC 2007 is the aggregation Economic activities are the same based on the following three priority criteria: Manufacturing processes and technologies delicate; Input materials that economic activities use to create products; Characteristics of the output of economic activity. In addition, a new trend in economic sub-sectors is emerging economic sectors. Emerging economic sectors are characterized by great growth potential, this is different from the economic sector is having a large growth rate. In these emerging economic sectors, the growth potential is still forecast, but these industries often grow faster than the common ground and lower than the economic sectors entering a high growth period. These industries often have the following characteristics to identify: (i) formed on the basis of new products, new services and new ideas resulting from changing customer needs, and often use as Key enabling technology; (ii) include entirely new industries, or more commonly, restructuring, integrating and converting old industries into new industries; (iii) tend to research and in-depth knowledge of the industry, because their appearance is often the result of creativity and innovation; (iv) this industry often has a combination of entrepreneurship and innovation, (v) they activate and allow changes in market structure, creating new suppliers, new customers, new business models, products and services; (vi) the emergence of this industry often creates breakthrough changes and affects the existence of other industries; (vii) and the industry tends to cluster highly, emerging industry companies tend to be geographically focused. Examples of current emerging technologies include educational technology, information technology, biotechnology, new materials technology, automation technology and artificial intelligence. And Silicon Valley is a valley in San Francisco USA is considered the paradise of startups, many businesses around the world gather here to start a business. According to a recent report by the European Union on emerging industries, these industries are often categorized according to the emerging technology that they apply, including seven main types of industry, such as: (i) environmental technology – Eco Industries; (ii) creative industries; (iii) maritime industries; (iv) mobility industries; (v) life science industries; (vi) information technology and (vii) services. In which Eco industry includes businesses providing innovative products and services that have a positive impact on the environment; Creative includes creative advertising, architecture, art, design, fashion, film, performance art, software, toys, games, etc Maritime industry includes companies providing innovative products and services related to the traditional maritime sector; the transportation industry includes products and services that optimize the time and journeys of goods and people; Information technology services sector includes companies providing new communication solutions. From the above concepts, the paper is based on the industry classification of Vietnam's Economic Sector System, and the trend of emerging industries temporarily categorizes the economic sectors that businesses innovate in Vietnam. These are agriculture technology, educational technology, financial technology, biotechnology and health, e-commerce, service technology and information technology. 2.3. Influence of industries on the efficiency of capital mobilization activities of startups A startup generally has an uncertain future, which is a risk for investors. However, the investor can assess the startup according to the market they (aim to) operate in. An often reported requirement of a VC investor is that the market of the startup allows for rapid growth ( ea, 19 ; Kaplan Str mberg, 2000). The investors require the growth of the firm to get a better return on investment. Investors are also, but less explicitly, attracted to startups that potentially create new markets or change existing ones (Kaplan Str mberg, 2000). The market opportunities influence all types of investments. However, they are more 142
5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 determining in early stage investments because startups not yet have a proven record in that stage. Vinig and De Haan (2003) show that investors in the Netherlands show special interest in startup in markets in which they are familiarized. In other words, investors target companies in specific industries. Multiple studies show different chances of attracting funding in different industries. Hellman and Puri (2000) discover that companies in the telecom and medical industry have more chance to attract funding, while this is less likely for companies in the computer industry. Chang (2004) recognized two categories of internet startups; e-commerce companies and internet platforms. The market for e- commerce companies proved to be more mature than the investment market for internet platforms. The study of Puri and Zarutskie (2012) showed that mainly companies in capital intensive industries, like electronics and biotech, are more likely to attract venture capital. Capital is indeed more abundant in the biotech industry; the companies in the sector are mainly targeted for their technology and product (Baum & Silverman, 2004; Ha ssler, 2009). The industries that were most present among the startups in both cities are included in the analysis; the analytics industry, FinTech industry and media / content industry. The media and content industry is a long established industry, advances in ICT have however led to an upturn of digital advertising (Simon et al, 2012; McKinsey & Company. 2015), The media industry is globally the same size as the FinTech industry, with both a transaction size of around 1,6 billion dollar (McKinsey & Company, 2015; SparkLabs, 2016). However, the online media and content is only a small share of the total industry. Moreover, the size of the FinTech industry is expected to grow 65% (Spark Labs, 2016) and the media industry merely 5% (McKinsey & Company, 2015). FinTech refers to financial technology; the industry consists of businesses that use software to provide financial services (FinTech Weekly, 2016). The funding of FinTech companies has risen 215% in Europe between 2014 and 2015, with the Nordics and the Netherlands as important sources (Accenture, 2015). The analytics industry consists of businesses that employ Big Data and/or Business Intelligence. Big Data is the information processing of complex voluminous data collections (Gartner, 2016a). Business Intelligence (BI) is a collection of applications, tools and other means for applying data in company operations (Gartner, 2016). The global Big Data analytics market has shown unparalleled growth, the market (measured in revenue) grew 260% from 7,6 billion dollar in 2011 to 27,4 in 2014 (Kelly, 2015). The growth is however projected to stabilize the coming years. This makes analytics startups in the sample of special interest, because they were in business during the period of the strongest growth. H1: The economic sector has an impact on the ability of creative startups to raise capital. H2: The economic sector has an impact on the efficiency of capital mobilization of creative startups. 2.4. Hypothesis Based on the theoretical basis, and measurement of the ability to raise capital and the efficiency of capital mobilization, the hypotheses are given as above. The paper uses the ability to raise capital and the efficiency of capital mobilization to measure capital mobilization activities of SMEs. Besides, the observed variable is the number of years of operation of the enterprise. Table 1: Summary of variables Variable Description Relationship expectation 1. Agri Equal to 1 if the enterprise belongs to agricultural +,+ technology, equal to 0 if not. 2. Ed Equal to 1 if the enterprise belongs to education +,+ technology, equal to 0 if not. 3. Fin Equal to 1 if the enterprise belongs to financial +,+ technology, equal to 0 if not. 143
6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 4. BioHeal Equal to 1 if the enterprise belongs to biology and +,+ health technology, equal to 0 if not. 5. Ecom Equal to 1 if the enterprise belongs to ecommerce, +,+ equal to 0 if not. 6. Sev Equal to 1 if the enterprise belongs to services +,+ technology, equal to 0 if not. 7. LogAge By Logarithm the years of foundation +,+ 8. Financing Equal to 1 if the enterprise belongs to financial +,+ technology, equal to 0 if not. 9.LogAmount By Logarithm the value of capital mobilization n/a 3. Data and methodology The research data of the project is taken from the CrunchBase database, from January 1, 2005 to December 31, 2018, including startups that have registered business establishment and are still operating to the present time. The sample collected includes 338 enterprises with complete information and data on the intended variable included in the regression model. Where Y (1) is Callability, which is inherently the identifier and Y (2) is Callability, which is inherently constant. The quantitative model for analyzing callability variables is the regression polynomial identifier model, the estimated model is the polynomial probit according to Finney (1952) because the dependent variable is a binary variable with only two values. are 0 and 1. Also the dependent variables are discrete and multi-cataloged variables. The project examines the impact of the economic industry on the efficiency of capital mobilization activities of creative start-ups. The SMEs are divided into seven sectors and take the biotechnology and health sectors as their base choices. Since the total probability of seven sectors is one, it is therefore not possible to estimate all probabilities independently, but the probability of biotechnology and health is determined automatically. The formula of the research model is as follows: Pi = Pr(Yi=1) = In which: Zi = B1 + B2Agrii+ B3Edu + B4Fin + B5Ecom + B6Sev + B7LogAge + ui Pi is the probability when Yi=1 (raised capital) Zi is a model to estimate the correlation between variables of different industries and the observed variable is logarithms of firm's age. To estimate the efficiency of capital mobilization of enterprises, the research team used a linear regression model to test, the formula as follows:Vi = B0 + B2Agrii+ B3Edu + B4Fin + B5Ecom + B6Sev + B7LogAge In which: Vi= Log(Amount of money startup raisingfund) The remaining variables remain the same. 4. Results and discussion Overview of the number of innovative start-ups during 2005-2018 by industries is as follows: 144
7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 2: Start-ups by industries from 2005 - 2018 Industry Number Percentage (%) Agritech 21 6.2% Edtech 32 9.5% Fintech 24 7.1% Biotech and health 26 7.7% Ecommerce 46 13.6% Services 132 39% Information technology 57 16.8% Total 338 100 Source: Crunch Base, 2019 The majority of SMEs focus on the next service (39%) technology and information technology (16.8%) and e-commerce (13.6%). The remaining industries account for over 30% with 103 out of 338 start-ups. It can be seen that new industries are still very potential in Vietnam market. Table 3: Number of deals that have been raised and failed to raise capital in the period of 2005-2018 Deals Number Rate Number of Start-ups who have mobilized capital but announced 84 25% the amount. Number of Start-ups have mobilized capital without disclosing 60 18% the amount. Number of Start-ups have not yet mobilized capital. 194 57% Total 338 100 Source: Crunch Base, 2019 It can be seen that the number of positive innovative startups in Vietnam, in the survey sample of 338 transactions, can be seen that the rate of successful capital-raising deals is 43%, which can be explained for this ratio as: The number of times a firm calls for capital is often large, so the loop increases but the actual number of businesses is lower than the number of deals. But this rate is positive for businesses when deciding to invest in innovative startups. Table 4: Descriptive statistics of quantitative variables Variables Std. Dev Min Max Age 5.868613 6.546332 1 14 LogAge .5553599 .4289468 0 1.272098 Amount 7,728,270 1.880000 1000 133,800,000 LogAmount 6.054553 1.047577 3 8.126456 145
8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Statistics from 2005 so the business year of the SME enterprises have 14 year old enterprises. However, often these enterprises raise capital at the time, unlike the SMEs in the world, this time is often slower than the world. The largest amount raised was Momo e-wallet, with 133.8 million dollars, through 04 rounds of fundraising. Table 5: Regression according to the variable Probit model depends on the ability of Startups financing Financing Std. Dev z P-value Agri .0557609 .5287425 0.11 0.916 Ed .4271508 .4703964 0.91 0.364 Fin 1.375533 .581254 2.37 0.018 Ecom 1.133812 .4635294 2.45 0.014 Sev .6450354 .4118661 1.57 0.117 IT .2422081 .4443437 0.55 0.586 LogAge 2.427081 .277799 8.74 0.000 LR-Chi square 140.77 Pseudo-R Square 0.3730 Observations 338 , P-value <0.05; 0.001 We see the model has only three significant variables, of which two variables have P-value <0.05 that is the Fin variable and the Ecom variable, 1 variable with P-value value <0.001 is the LogAge variable. Thus, the results show that assumptions about the SMEs in the financial technology industry, e- commerce and the observed variable of years of operation of enterprises have an impact on the ability of enterprises to raise capital. Enterprises in the financial technology industry have a higher probability of raising capital than enterprises in the biotechnology and financial industries. Pi regression parameters here are 1.37 and z = 2.37, which means that enterprises involved in financial technology, the ability to raise capital increased 1.37 times. This result is consistent with the theory that the number of investment deals in the financial sector has been increasing in recent years, and the market of this industry is still very large and the solution. The technology has become very useful when applied to financial sector startups. Through Figure 5, the regression parameter of the Ecom variable is positive and at 1.133, businesses in the e-commerce industry have an advantage in the ability to raise capital with the remaining industries. This result supports the judgment of Yang (2015), that the ability to mobilize capital of innovative start-ups in the e-commerce industry is influenced by industry and environmental factors. business. It can be seen that in the opposite direction, enterprises in the e-commerce industry will have advantages for better business operations, higher ability to raise capital. A result with p-value <0.001 is the number of years of operation of the enterprise, this ratio shows the statistical significance of the business age variable is very large. This is also true compared to previous studies and also almost obvious. The longer a business, especially the startups, the longer its operating time, the better its ability to do business, the better its ability to do business, the higher its ability to raise capital. Next, examine the regression model on the efficiency of capital mobilization activities of the startups by sectors. 146
9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Table 6: Regression of linear model of industry influence on capital mobilization efficiency of SMEs Amount of Std. Dev t-stat P-value Financing Agri -.3991785 .7626101 -0.52 0.602 Ed .169757 .630623 0.27 0.789 Fin .8895705 .6702611 1.33 0.189 Ecom .9185335 .588869 1.56 0.123 Sev 1.062981 .5616084 1.89 0.062* IT .7256238 .6213987 1.17 0.247 LogAge .7938875 .2710732 2.93 0.005 Prob > F 0.00098 R- Square 0.2809 Obs 84 *, P-value < 0.1; 0.05 According to the table above, the results of estimating the regression model depending on the capital mobilization value of the SMEs by economic sector have two significant variables, namely the Sev variable - service technology with P-value < 0.1 (0.062) and the LogAge variable (0.005 <0.05). It can be seen that, in terms of capital mobilization efficiency, enterprises in the service sector mobilize a larger amount of capital compared to enterprises in the remaining industries. Explaining this, it can be seen that the number of service sector deals accounts for a large proportion in the observed sample, because when the economic sub-sector, the financial sector is much narrower than the tourism service sector and transport services. However, because the resources invested in transport and tourism services need more capital than the financial industry, the amount of capital invested in the service industry is understandable. Age is a strong factor in raising large capital (0.81), because the more businesses start up, the more investment they need, and the more trust they have built in investors then they will get the fastest and the right amount as they expected so here the age of the business has a strong correlation and a great impact on the amount of capital raised by the business. Through two research models of capital mobilization and capital mobilization efficiency, we can see that there exists a relationship between economic sectors and capital mobilization activities. More specifically, in the context of the Vietnamese market, industries such as financial technology, e- commerce, and service technology are the sectors that attract the most investment capital of investors. On the other hand, the number of years of operation of an enterprise is proportional to both the ability and effectiveness of capital mobilization of SMEs in Vietnam. 5. Conclusion and limitations Research paper on capital mobilization activities of innovative startups in Vietnam has shown the influence of factors on the ability and capital mobilization activities of innovative startups. In which, important factors to be considered are: Business sector and the age of the business. Among these factors, business factors have a great influence and need to be focused, because each business has its own characteristics and needs a different amount of capital to maintain operations. The age of the business also plays an important role in raising funds for the organization. The results show that businesses with longer operating time will need more capital and also easier to raise capital. 147
10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2019 ICYREB 2019 Research on innovative start-up businesses in Vietnam is inherently a new research problem, so it is difficult for the authors to avoid some difficulties during the research process. Because of the difficulty in collecting and refining data, the article only analyzes the impact of three main factors: industry, model and age of innovative start-ups to capital mobilization. without research further combined with other impact factors. Data of Vietnamese enterprises has not been published really accurate compared to reality, because many of the information is either theoretical or unreasonable. The research paper tried to screen and minimize as many false figures as possible but certainly could not avoid errors. Entrepreneurs and those who plan to start a business in the future will have more useful knowledge about raising capital for businesses. REFERENCES [1] Accenture (2015). The Future of Fintech and Banking: Digitally disrupted or reimagined? London: Accenture. [2] Aldrich, H. and Wiedenmayer, G., 1993. From traits to rates: An ecological perspective on organizational foundings. J. Katz, R. Brockhaus, eds. Advances in Entrepreneurship, Firm Emergence, and Growth, Vol. I. [3] Bates, T. (1990), “Entrepreneur human capital inputs and small business longevity”, Review of Economics and Statistics, Vol. 72 No. 4, pp. 551-559. [4] Baum, J. A. & Silverman, B. S. (2004) Picking winners or building them? Alliance, intellectual, and human capital as selection criteria in venture financing and performance of biotechnology startups. Journal of business venturing, 19(3): 411-436. [5] Bergvinson, D (2018) Science & Technology and Startups in Agriculture. In: National Conference on Agriculture 2022 - Doubling Farmers' Income, February 19 - 20, 2018, New Delhi, India. [6] Chang, S. J. (2004) Venture capital financing, strategic alliances, and the initial public offerings of Internet startups. Journal of Business Venturing, 19(5): 721-741. [7] Clarysse, B., Bruneel, J. and Wright, M. (2011), “Explaining growth path of young technology- based firms: structuring resource portfolios in different competitive environments”, Strategic Entrepreneurship Journal, Vol. 5 No. 2, pp. 137-157. [8] Cressy, . (1996), “Are business startups debt-rationed?”, Economic Journal, Vol. 106 No. 438, pp. 1253-1270. [9] Crunchbase (2019) Search. Available at: [Accessed 1-3-2019]. [10] Davidsson, P. and Honig, B., 2003. The role of social and human capital among nascent entrepreneurs. Journal of business venturing, 18(3), pp.301-331. [11] Ernst & Young, 2017. BioTech Report 2017: Beyond Borders. [12] Finney, D.J. and Tattersfield, F., 1952. Probit analysis. Cambridge University Press; Cambridge. [13] FinTech Weekly (2015) FinTech definition. Available at: /fintech-definition [Published: 27-5-2016]. [14] Gartner (2016) Business Intelligence (BI). Available at: glossary/business-intelligence- bi/ [Accessed 27-5-2016]. [15] Haltiwanger, J., Jarmin, .S. and Miranda, J. (2013), “Who creates jobs? Small vs large vs young”,The Review of Economics and Statistics, Vol. XCV No. 2, pp. 347-361. [16] H ussler, C. Harhoff, D. M ller, E. (2012) To Be Financed or Not -The Role of Patents for Venture Capital Financing. ZEW-Centre for European Economic Research Discussion Paper, (09-003). [17] Hellmann, T. & Puri, M. (2000) The interaction between product market and financing strategy: The role of venture capital. Review of Financial studies, 13(4): 959-984. 148
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