Does Information Asymmetry Influence Hi-tech Entrepreneurial Financing?

Exploring the effective ways of start-up financing is an important and practical issue to technological innovation and economic development. This paper aims to investigate the impacts of information asymmetry on the high-tech start-up financing preference, and whether an entrepreneur’s internationality features moderate the main effects. A sample of 500 high-tech start-ups and new ventures was collected at Shenzhen, China. Regression models are designated for testing both the main effects predicted in research hypotheses and the predicted moderating role of an entrepreneur’s internationality features. Our test results lead to 3 findings: firstly, in the high-tech industries, the information asymmetry mitigated by disclosing intellectual properties can significantly increase the start-up preference for external financing. This finding can be explained by the reduction of agency costs of debts. Secondly, the lessened information asymmetry can shorten the life cycle of start-up financing under the pecking order hypothesis. Lastly, the liability of foreignness is observed to have a significant positive moderating role on the main effects under the investigation. It can be concluded that the information asymmetry and the liability of foreignness are crucial factors influencing start-up financing decisions. This conclusion implies that reducing the information asymmetry by adequately disclosing technological strength and tacit knowledge can benefit the entrepreneurial financing for the high-tech start-ups and new ventures at the early stages, as well as provide an effective shortcut to the start-up financing cycle. Furthermore, the introduction of overseas technologies, funds, knowledge, experiences, and


Introduction
While the large-size multinational companies have long caught the limelight of academic research in the fields of international business and globalization, the small and medium hi-tech startups and new ventures have become a critical part of the growth engine in most economies of the world (Ng & Kee, 2017  However, vigorous small and micro hi-tech startups and new ventures have financial constraints in their inception, survival, and growth. Early-stage funding is a critical issue for most of them. Hanson (1983) points out that lack of adequate entrepreneurial financing sources is the major obstacle to the survival and growth of startup businesses. In practice, the hi-tech startup"s urgent demand for entrepreneurial financing stands out in the way of early-stage survival and growth. The key source of the financing difficulties confronting the startups and new ventures is the information asymmetry between the financiers and the firms who need to obtain entrepreneurial financing. Entrepreneurial finance is a distinctive aspect of corporate finance, notably concerning informational asymmetries.
Great pressure and obstacles are reported in a vast body of entrepreneurial financing research on the emerging market such as China, especially for those small and micro hi-tech startups, they are rarely considered by the funding and financing sources in the external capital markets. As the most important innovation center of the Great Bay Area (GBA) in southern China, Shenzhen is a pioneering city in China, offering researchers a rich data source of natural experiments in entrepreneurial financing and hi-and new-tech new venturing. The industrial development policies of both the Central government and local governments have clearly articulated their support for innovation and entrepreneurship which play vital roles in sparkling the developments of economy, science, and technology. Namely, the Fintech-based financial industry and innovation-led technical breakthroughs are the keynotes in the blueprint for future reforms. The implementation of these innovation and entrepreneurship encouraging policies has created a good chance for combining academic research with practical applications and explorations.
As it happens elsewhere in the world, hi-tech startups and new ventures are always confronted with various difficulties in sourcing their entrepreneurial finance. Exploring the effective ways of startup 12 Published by SCHOLINK INC. loans to the startups. Wu et al. (2008) clarify two major lending techniques in China, one being transactional lending based on quantitative data such as the asset-guaranteed or financial statement, and the other, relationship lending that refers to the lending based on the qualitative information usually acquired through interpersonal contacts and communication.
The larger information asymmetry leads to higher agency costs of debts and equity, which influences the entrepreneurial preference for financing resources, in terms of selection between internal and external sources, and the total amounts expected to acquire. On the other way around, the voluntary disclosure of technological competitiveness and tacit knowledge advantages is conjectured to lessen the information asymmetry thus reducing the agency costs of debts, especially the external financing sources. Therefore, I propose the following two research hypotheses: H1a: The more information disclosure regarding the intellectual properties, the larger amount of funding the startup entrepreneur requests from external sources.

H1b:
The more information disclosure regarding the firm-specific tacit knowledge, the larger amount of funding the startup entrepreneur requests from the external sources.

Pecking Order Hypotheses (POH) and Entrepreneurial Financing Preferences
The pecking order theory arises from information asymmetry. Myers and Majluf (1984) argue that owing to the information asymmetries between the firm and potential investors, managers have more inside information than investors and act in favor of old shareholders. The pecking order theory suggests that a firm usually has a specific preference order for its capital structure decisions, i.e., the firm will prefer retained earnings to debt, short-term over long-term debt, and debt over equity. Thus, the pecking order theory fits well in the explanation of the startup"s financing preference in that it assumes that there is no target capital structure which is very common in startups and new ventures.
The firms choose entrepreneurial financing sources according to the following preference order: internal finance, debt, and equity. Wu et al. (2008) and Robb and Robinson (2014) also document some evidence on the pecking order hypothesis on the firm"s financing structure and techniques. According to their findings, Chinese startups mainly use their wealth and family financial sources to fund their business at the inception and surviving stages, while they tend to seek external funds, especially the intermediated finance such as bank loans when they enter the growth period.
Other research results show strong consistency with the pecking order theory. Chua et al. (2011) find a positive association between family involvement and new venture debt financing. Åstebrol and Bernhardt (2003) conclude that the startups having a bank loan are significantly less likely to survive than those having a non-bank loan. Honjo and Nagaoka (2003) conclude that the startups with the financial support of venture capitals and the technological support from universities are more likely to go public earlier than other counterparts. Daskalakis et al. (2013) argue that startup entrepreneurs are www.scholink.org/ojs/index.php/jar Journal of Asian Research Vol. 5, No. 4, 2021 13 Published by SCHOLINK INC. reluctant to use new external equity financing because they rely heavily on their family or personal funds and dislike the dilution of equity via raising new equity sources, on the other, the startup entrepreneurs prefer to borrow from external sources, especially the long-term debt financing.
Furthermore, the pecking order theory implies that there are stages of entrepreneurial financing for the startups. Chemmanur and Chen (2006)  Thus, the following research hypotheses are proposed for empirical tests: H2a: The more information disclosure regarding the intellectual properties, the more likely it is for the startup entrepreneur to adopt a staged external financing plan.
H2b: The more information disclosure regarding the firm-specific tacit knowledge, the more likely it is for the startup entrepreneur to adopt a staged external financing plan.

H2c:
The more information disclosure regarding the intellectual properties, the more likely it is for the startup entrepreneur to seek the external, especially the equity-based external sources.

H2d:
The more information disclosure regarding the firm-specific tacit knowledge, the more likely it is for the startup entrepreneur to seek the external, especially the equity-based external sources.

Liability of Foreignness
The liability of foreignness refers to the costs that foreign firms incur or the benefits that are available to domestic firms but not to foreign firms (Rugman & Verbeke, 2007). Guar et al. (2011) argues that there are two sources of liability of foreignness-environmentally derived liability of foreignness and firm-based liability of foreignness. Mo and Kurt (2018) investigate the relationship between the liability of foreignness and the openness of the entrepreneur"s social network and conclude that the increasing cost of entering a foreign market due to the closed network worsens the liability of foreignness.
Some research papers focus on the foreignness liability issue confronting firms in China. Ng and Curran (2017) study the liability of foreignness confronting the foreign companies operating in China, and they find out that the most persistent problems include the use of the local employees and developing relationships with both national and local governments. Most Chinese international business scholars tend to highlight the positive role of foreignness liability in terms of returnees or returnee entrepreneurs. Qin et al. (2017)  their home country to start their new ventures, and they explain that the liability of both newness and foreignness plays a crucial role in slowing down the returnee"s speed of entrepreneurial entry. Bai et al. (2017) investigate the impact of returnee entrepreneurs" international experience and knowledge on the initial and early international expansion of the returnee entrepreneurial firm and argue that the returnee"s international experience nurtures knowledge about international markets and in turn produces a positive effect on the level of internationalization.
To accommodate the theme of hi-tech startup financing, this study considers returnee entrepreneurship an appropriate proxy for us to investigate the moderating role of foreignness liability on the main effects. In practice, returnee entrepreneurs represent the various entrepreneurial inputs flowing back to China, including new products, new technologies, innovations, advanced managerial experience, financial and human resources. Therefore, I propose the following research hypothesis.

H3:
Returnee entrepreneurship, a proxy for the liability of foreignness, significantly moderates the main effect between the information asymmetry reduction via disclosure and the entrepreneur"s financing preference for external sources (including the requested amount, the staged plan, and equity-based financing). Though there is a vast body of existing literature dedicated to entrepreneurship research and a large number of studies on entrepreneurial financing, there are some gaps to fill up in these academic fields.

Figure 1. Conceptual Framework in this Study
First, the entrepreneurial financing issue for hi-tech startups has seldom been visited. Second, the association between the pecking order hypothesis and the information asymmetry has not yet been tested empirically. Third, the liability of foreignness has not been introduced into the existing entrepreneurial financing literature.
To bridge the foregoing literature gaps, this study develops a conceptual framework for the further investigations of the rationale for the entrepreneurial financing preferences in the hi-tech startups, based on the theoretical explanations of information asymmetry, the financing cycle under the pecking order hypothesis, and the potential impact of the foreignness liability. This framework is illustrated in Figure 1.

Data Collection
Following

Research Variables and Measurements
The research variables investigated in this study fall into four categories. Firstly, the dependent variables include the entrepreneur"s selection between external and internal financing sources, the pecking order hypothesis, and the external financing sources requested. Secondly, two explanatory variables are selected to act as proxies for the two key dimensions of the information asymmetry, i.e., the technological uncertainty and managerial tacit knowledge, which are identified and measured by the content disclosure in the startup business plans. I follow the existing startup and entrepreneurial financing literature to select the control variables crucial to our regression tests.

Dependent Variables
The dependent variables are related to the startup financing preference, including four variables for the entrepreneur"s preference for external financing sources, the staged external financing plan, the involvement of equity transferring, and the dollar value of the expected external financing. These four dependent variables are denoted by FINPRF, STAGEDFIN, EQUITYFIN, and LGFIN$ respectively.

Explanatory and Moderating Variables
We use two sets of explanatory variables as proxies for the lessening of the information asymmetry: one is related to the technological uncertainty, and the other is relevant to the firm-specific knowledge.
The first set includes the information disclosure regarding the two types of intellectual properties, and the number of the officially approved and authorized intellectual properties, denoted by IPTYPE and IPNO respectively. For the second set, I choose the number of years for which the key startup team members have worked for the new venture and this variable is denoted by TACITYEAR.

Control Variables
The first control variable in this study is firm size. Colombo and Grilli (2005)  We also control the industry factor. All the hi-tech startups in this study are classified into 6 groups of   The last control variable is the wealth of the startup entrepreneurs. As it is studied in Frid et al. (2016), the wealthier entrepreneurs are more likely to obtain larger amounts of external findings while the low-wealth ones are more likely to be rejected by the banks and other external financiers.
In summary, for our study on entrepreneurial financing, I try to control those factors which might influence our results. They are denoted by SIZE, EDUCATION, INDUSTRY, POLITICS, and WEALTH. Table 1 summarizes all the research variables used in this study.
LGFIN$=β 0 +β 1 I PTYPE(IPNO, TACITYEAR)+β 2 RETURNEE +β 3 CROSSITEM i +β k ΣControls + ɛ (Models 4,5,6)    Notes. * significant at 0.10, ** significant at 0.05, and *** significant at 0.01. Table 4 presents the results of regression models for testing the relationships between the three financing preference variables and the three explanatory variables for the two aspects of information asymmetry. There are significant positive correlations between the requested amount of external financing sources and the content disclosure of the number of intellectual properties and the firm-specific managerial experience with the startups and new ventures. Hypotheses H1a and H1b are supported except for the non-significant positive correlation effect for the variable IPTYPE.  Model fit summary R 2 =.542

Regression Tests on the Main Effects (H1s and H2s)
Adjusted R 2 =.479 Sig.=.000 n=500 Cox & Snell R 2 =.404 Nagelkerke R 2 =.543 Sig.=.000 n=500 Cox & Snell R 2 =.404 Nagelkerke R 2 =.543 Sig.=.000 n=500 Our findings are consistent with the conclusion in Leonard and Sensiper (1998), Li and Gao (2003), and Nofsinger and Wang (2011), which show that the key external financiers such as banks and institutional investors concentrate their due diligence upon the information asymmetry problems when they deal with the initial startup funding. However, our investigation further differentiates the different dimensions of information asymmetry by using the three operationalized proxies in terms of content disclosure about the intellectual properties.
The exception means the two types of intellectual properties, i.e., application versus invention, are not differentiated in the hi-tech startup financing decisions. This finding leads to our preliminary conclusion that in the entrepreneurial financing decisions, the hi-tech startups tend to pack up their intellectual properties as an entirety in their content disclosure. The external financiers need to be better informed of the details to release their concerns regarding the technological uncertainties.
It is noteworthy that the control variables of SIZE, EDUCATION, PCONNECTION, and WEALTH are significantly correlated to the dollar value requested in the hi-tech startup financing. This finding is consistent with the conclusions in the existing literature (e.g., Haines et al., 1989;Nofsinger & Wang, 2011), which helps to add incremental validity to the empirical test results in this study. On the other hand, the empirical tests on hypotheses H2s produce the identical results with H1s in terms of TACITYEAR, which means the more experienced startups are more likely to prepare the staged external financing plan, particularly designing the equity-based financing schedule to mitigate the agency problems in the hi-tech startup financing. It can be concluded here that the reporting of the firm-specific managerial experience with startups and new ventures, instead of content disclosure of intellectual properties, is the preferred way of lessening the information asymmetry in startup financing.
In  As presented in the foregoing empirical results and analyses on H1s and H2s, the expected moderation role of the foreignness liability is significantly pronounced on the main effects between the amount requested for external financing and the proxies for the lessening of information asymmetry. Table 5 presents the further test results regarding this moderation. For all the three interactions between RETURNEE and the information asymmetry proxies, the coefficients are significant, especially for the IPNO and TACITYEAR (both significant at the 0.01 level).

Conclusions
The technology-led information asymmetry mitigated through the appropriate disclosure of the Our empirical results support our research hypotheses on the relationship between the lessening of information asymmetry and the hi-tech startup financing preferences, especially those for the staged and equity-based external financing. I also document the evidence for the shortened financing cycle for the hi-tech startups under the pecking order hypothesis. This is largely consistent with the reality of hi-tech entrepreneurship. The startups at the inception stage, i.e., less than 1 year old, mainly rely on the founder"s wealth and family/partner financial support, seek less amount and simpler ways of external funds compared with the startup at the survival stage, i.e., more than 1-year-old. At the survival or growth stage, the startups who usually have some existing external financing sources, tend to seek a larger amount of external funds and more sophisticated financing alternatives.
This study draws three conclusions: firstly, in the hi-tech industries, the information asymmetry mitigated by the content disclosure regarding the intellectual properties and the management-specific tacit knowledge can significantly increase the startup preference for the external financing due to the reduction of agency costs of debts; secondly, the lessened information asymmetry can shorten the life cycle of startup financing under the pecking order hypothesis, and lastly, the liability of foreignness is observed to have a significant positive moderating role on the main effects under the investigation. In summary, it can be concluded that the information asymmetry and the liability of foreignness are crucial factors impacting the startup financing decisions. micro and small firms of this type are not exposed to this specific business competition and they do have different preferences for startup financing.

Limitations
The data collection is based on the manual reading and coding of the business plans presented by the hi-tech startups and new ventures. If some artificial intelligent way of data mining could be used given the uniform business plan presentation formats, then the results covering the entire hi-tech startup population would bring up more convincing power to this research report.

Implications
This study contributes to the existing entrepreneurial financing literature with certain unique academic implications. First, it inspires to explore more social-psychological aspects of the startup financing preferences; second, it suggests utilizing more research methods, e.g., questionnaire surveys and in-depth interviews, and last, it implies that more theoretical perspectives should be introduced into the investigation of the rationale for the startup financing preferences.
There are some practical implications as well. The conclusions of this study imply that reducing the information asymmetry by adequately disclosing technological strength and tacit knowledge can benefit the entrepreneurial financing for the hi-tech startups and new ventures at the early stages, as well as provide an effective shortcut to the startup financing cycle. Additionally, the introduction of overseas technologies, funds, knowledge, experiences, and entrepreneurship into the hi-tech startups does not create the liability of foreignness, and on the contrary, it is an "asset" that can help improve the entrepreneurial financing decisions. Furthermore, different groups of stakeholders might infer some implications from the conclusions of this study: for the hi-tech startup and new venture entrepreneurs, they are inspired to plan for the staged external entrepreneurial financing, especially the equity-based financing, at the earlier stages; for the financiers, they might learn how to identify and match the appropriate financing needs of various types of hi-tech startups and new ventures; for the policymakers and government monitory agencies, they need to provide guidance and supervision on the innovation-capital matching effectiveness, and to better the financial and capital market environment for startup financing for innovations and entrepreneurship.