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Journal of Science and Technology Policy Management Small and medium technology enterprises in Zhongguancun and Silicon Valley: Regional innovation system approach Anna Trunina, Xielin Liu, Jian Chen,

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Article information: To cite this document: Anna Trunina, Xielin Liu, Jian Chen, (2018) "Small and medium technology enterprises in Zhongguancun and Silicon Valley: Regional innovation system approach", Journal of Science and Technology Policy Management, https://doi.org/10.1108/JSTPM-01-2018-0006 Permanent link to this document: https://doi.org/10.1108/JSTPM-01-2018-0006 Downloaded on: 26 May 2018, At: 02:23 (PT) References: this document contains references to 60 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 1 times since 2018* Access to this document was granted through an Emerald subscription provided by

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Small and medium technology enterprises in Zhongguancun and Silicon Valley

Regional innovation system approach

Regional innovation system approach Downloaded by GRADUATE SCHOOL, Anna Trunina At 02:23 26 May 2018 (PT)

Anna Trunina and Xielin Liu School of Economics and Management, University of Chinese Academy of Sciences, Beijing, China, and

Received 14 January 2018 Revised 16 April 2018 Accepted 25 April 2018

Jian Chen Chinese Academy of Science and Technology for Development, Ministry of Science and Technology, Beijing, China

Abstract Purpose – The purpose of this paper is to contribute to the understanding of similarities and differences between small and medium technology enterprises of Zhongguancun in China and Silicon Valley in the USA in the following aspects of their activities: scale, diversity and the strength of entrepreneurial networks; quality of collaboration network; reputation in the sense of stakeholders’ perception at the local market; and foreign networks. Design/methodology/approach – The study uses a survey method. The analysis of variance statistical technique was applied to each aspect. Findings – The investigation reveals that Chinese companies have more stakeholders among relatives and friends, government, universities, accounting/law, as well as collaborate more with competitors and suppliers, while the US companies have more and collaborate diverse relations with its clients. In America, companies tend to trust their partners more than they do in China. For Chinese companies, the local government appraises business more than the USA. Employees from the US companies also take more pride in telling others that they are members of the business. Domestic customers positively rate business products. Chinese companies actually have better access to foreign resources than the USA and collaborate more with their foreign stakeholders. Practical implications – Understanding the distinctive features of each regional system is crucial for the success of small and medium technology enterprises for both Chinese and US entrepreneurs. Originality/value – This paper is a pioneer in the comparison and analysis of the two regions.

Keywords Collaboration network, Silicon Valley, Small and medium technology enterprises, Zhongguancun Paper type Research paper

1. Introduction Silicon Valley is the world’s most dynamic economic region as it is a habitat for innovation and entrepreneurship. Its dense of industrial networks, knowledge intensity, community

The authors want to thank all respondents participated in the survey. This work was supported by CAS–TWAS President’s Fellowship. The authors would like to thank two anonymous reviewers for their comments and suggestions.

Journal of Science and Technology Policy Management © Emerald Publishing Limited 2053-4620 DOI 10.1108/JSTPM-01-2018-0006


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dynamics among business, governments and other sectors, high-quality labor markets and the supply of VC encourage entrepreneurship and experimentation (Wonglimpiyarat, 2006). The present region’s exceptional culture, professional networks and industry leadership help attract and retain talented and ambitious clientele. Large-scale exits and breakneck growth are a daily business in the Bay Area. Despite a drop by more than 10 per cent, more than a third of the global value creation existing in 2017 is still captured in Silicon Valley. At the same time, Silicon Valley will continue to face pressure from the growth of another startup ecosystem. Overall, the venture funding fell – Silicon Valley technology start-ups raised over a quarter less of the venture capital funding in 2016 than they did the year before. There are many top-tier papers and articles characterizing the specific features of Silicon Valley. The most powerful contribution to the understanding of innovation activities in this region is written by Anna Lee Saxenian, Martin Kenney, Chris Benner, etc. Zhongguancun is the most intensive scientific, education and talent resource in China. It boasts almost 40 colleges and universities such as the Peking and Tsinghua Universities, more than 200 national (municipal) scientific institutions such as the Chinese Academy of Social Sciences and the Chinese Academy of Engineering, 67 state-level laboratories, 27 national engineering research centers, 28 national engineering and technological research centers, 24 university S&T parks and 29 overseas student pioneer parks. TusPark is an important platform for Tsinghua University to promote regional innovations. Many of the high-tech enterprises that populated Beijing’s Zhongguancun regions in the 1980s and 1990s were spin-offs from universities and research institutes, including some that are now leading the information technology companies such as Lenovo, Founder and Shuguang. On March 13, 2009, the State Council approved the construction of the Zhongguancun National Demonstration Zone, and made the plan to build Zhongguancun into a science and technology innovation center with a global influence. The Development Plan Outline for Zhongguancun National Demonstration Zone (2011-2020) was launched by the State Council on January 26, 2011, marking a new starting point for Zhongguancun’s development. Currently, Zhongguancun is home to ten parks, namely, Haidian, Fengtai, Changping, Electronics City, Yizhuang, Desheng, Yonghe, Shijingshan and Tongzhou Parks as well as the Daxing Biomedicine Industrial Base. Zhongguancun’s venture capital cases and investment amount every year account for about a third of the country’s total. Today, the number of listed companies in the zone adds up to 189, comprising 113 domestic and 76 overseas companies. The characteristics of Zhongguancun are also well-shown in the publications of Cong Cao (2004), where he concluded the lack of institutional support and technology capabilities; Tan (2006), where she examines the growth of the cluster and challenges firms face. Several authors found many similarities in terms of development and innovation creation between Zhongguancun and Silicon Valley. It resembles in its labor mobility, youthful energy, devotion to technology (Zhou, 2005) and close connections with the universities and research institutes. On the other hand, a lot of differences can be seen in these areas in terms of innovation initiator, early technology adoption culture, a culture of accepting failures and mutual help. Some comparisons parameters are presented in Table I. Both Zhongguancun and Silicon Valley are the regional innovation systems (RIS) of China and the USA accordingly. RIS is one of the most influential concepts developed in the context of regional science studies. According to the definition given by Cooke (2004) RIS is “interacting knowledge generation and exploitation subsystems linked to global, national and other regional systems”. The regional level and specific local and regional resources may still be important in firms’ effort to obtain global competitiveness. The main types of RIS include territorially


Parameters

Zhongguancun

Silicon Valley

Location Development year Key Initiator of Innovations Number of technology organizations in the region Ecosystem value Leading scientific institutions of the region

Beijing, China Mid-1980s Government 4,800-7,200, the third largest startup output in the world $131bn Peking University, Tsinghua University, Chinese Academy of Sciences, etc 23 per cent 32 (the fifth youngest in the world) Lenovo (CAS Institute of computing technology); Founder (Peking University), Stone Group; and Datang Telecommunications Technology (China Academy of Telecommunication Research)

Bay Area, California, USA 1940s Market 12,700-15,600 and two million tech workers $264 bn U.C. Berkeley, Stanford, U.C. San Francisco, etc

Immigrant founders Founder average age Example of scientific institution-affiliated enterprises


46 per cent 36.2 Google, iRobot (Stanford)

embedded regional innovation networks; characterizing by geographical, social and cultural proximity; regional networked innovation systems, characterizing planned, systemic networking; and regionalized national innovation systems, which involve individuals with the same education and common experiences (Asheim and Isaksen, 2002). Also, technology companies in their early-stage development are very dependent on their surroundings in the system. RIS have different characteristics in different regions. A Global Startup Ecosystem report 2017 showed the distinctive features of each ecosystem in 20 different cities of the world comparing such characteristics as performance, funding, market reach, talent and experience. The purpose of this paper is to contribute to the understanding of the similarities and differences between the Chinese and US small and medium technology enterprises located in both Zhongguancun and Silicon Valley. Previous research about these regions focus more on challenges of the firms caused by market, government and institutional issues, but there is a research gap characterizing how the small and medium technology enterprises behave within their innovation systems (for Chinese enterprises in Chinese ecosystem and American enterprises in the US system), such as scale, diversity and the strength of entrepreneurial networks in China and the USA, quality of collaboration network, reputation in the sense of stakeholders’ perception at the local markets and foreign network for the US and Chinese small and medium technology enterprises. Each of these factors contributes to the following explanation: The scale, diversity and the strength of entrepreneurial networks will show the number of stakeholders involved in the work with small and medium technology enterprises and the collaboration frequency between each other. The quality of collaboration network shows how the company collaborates with the others, i.e. if the companies trust to the other stakeholders and how they maintain the relations. The parameters of reputation in the sense of stakeholders’ perception at the local markets show how other stakeholders are related to the small or medium technology enterprises.

Table I. Comparisons parameters: China vs USA


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Foreign network parameters will show if it is easy to access foreign resources and how frequently companies collaborate with their foreign stakeholders.

In this paper, for the research of Chinese small and medium technology enterprises, the National Bureau of Statistics of China’s definition of small and medium enterprise was adopted: “Medium-sized enterprise – the enterprise with annual turnover of 30 to 300 million RMB and/or 300 to 2,000 employees; and small-sized enterprises – the enterprise with annual turnover of less than 30 million RMB and/or less than 300 employees”. In the USA, the definition of a small and medium enterprise varies by industry, based on the North American Industry Classification System (NAICS). Analyzing the most technology industries the defined small and medium enterprise definition for the US enterprises includes all enterprises with fewer than 500 employees and in the $7 million and under annual revenue threshold. The remainder of this paper is organized as follows: Section 2 shows the conceptual framework. Section 3 presents the literature review of each of the four factors. Then, the research design and analysis of the results, methods of data collection are presented in Sections 4 and 5, followed by the conclusion and implications of the study in Section 6. 2. Theoretical framework Small and medium technology enterprises are the main source of technical innovations (Lyasnikov et al., 2014). Enterprises do not exist in isolation. Any regional innovation system is based on several key stakeholders (Asheim et al., 2011; Nelson and Winter, 1982; Edquist, 1997), and therefore, the entrepreneurial network can involve such stakeholders as follows: Scientific institutions: universities, academy of sciences and research institutes are the main suppliers of innovative ideas for the commercialization, development of top talents and formation of teams for innovative organizations, as well as scientific and technical expertise and knowledge (Asheim and Coenen, 2005). Investment companies (mainly venture capital funds): these are responsible for the attraction of financial resources and business competencies required for the development of innovative companies and turning them into full-fledged business. Infrastructure: it contributes to the creation of favorable conditions for the existence of innovative organizations. It can be both material (industrial parks, business incubators, technology development centers, science parks, etc.) and intangible (services for the protection of intellectual property, the promotion of innovative products to foreign markets, outsourcing “non-innovative” aspects of the work, etc.). Industry: this is a manufacturer of high technology products and creates demand for innovative technologies and small businesses with all of their development and intellectual property. Government institutions: these create comfortable working conditions not only for innovative organizations, but also for all participants in the system, and define the convenient rules of the game, allowing them to build a reasonable balance of interest between various players in the market. At the regional level, collaborating small and medium enterprises with universities, research centers, government officials, corporations and other regional entities is very important to foster innovation, understanding transfer and human resource development. According to Liu and White (2001), regional collaboration among stakeholders fosters the improvements


of innovation capabilities. The influence of each stakeholder in China and the USA is different. Therefore, we use these five groups of stakeholders (i.e. scientific institutions, investment companies, infrastructure, industry and government institutions) to examine the small and medium technology enterprises in four aspects described above. Examination means that within this research we compare the following: (1) Chinese and American small and medium technology enterprises regarding how many stakeholders (i.e. scientific institutions, investment companies, infrastructure, industry and government institutions) the companies collaborate with; and compare how often Chinese and American small and medium technology enterprises communicate with the stakeholders of RIS (i.e. scientific institutions, investment companies, infrastructure, industry and government institutions); (2) the quality of collaboration for Chinese and American enterprises, i.e. identify how the companies build the relations with their stakeholders (i.e. scientific institutions, investment companies, infrastructure, industry and government institutions) during the collaboration; (3) reputation, i.e. how the stakeholder relates to the Chinese and American companies accordingly as reputation plays a significant role and can influence the behavior of stakeholders (Agostini and Nosella, 2016; Strobl and Peters, 2013; Gatzert, 2015); and (4) the collaboration of Chinese and American small and medium technology enterprises with the foreigner innovation systems, i.e. collaboration with stakeholders and ability of getting the resources. In knowledge-based economies, the interactions among different stakeholders within the innovation system are crucial to promoting competitiveness through technological improvements and innovations. The key stakeholders of the regional innovation system and the relationships between them are shown in Figure 1. An initial stakeholder value network analysis demonstrates the important links between the five key groups of stakeholders listed above. Small and medium technology enterprises will be effective if there are strong relations between all stakeholders of the system (Lundvall, 1992) and firms and knowledge organizations interact systematically. The advantages associated with small and medium technology enterprises are those of entrepreneurial dynamism, internal flexibility and responsiveness to changing circumstances. The region’s dense social networks encourage entrepreneurship (Saxenian, 1996). Geographical concentration can facilitate exploitation of knowledge spillovers because it helps to maintain more formal ties and interact more frequently, getting better access to informal informational networks and information transfer across organizational boundaries (Tan, 2006). The clustering of high-technology firms and the synergies it creates among various institutions in the cluster is a defining characteristic of the Silicon Valley (Hu, 2007).

3. Literature review The present study aims primarily to investigate the differences between Chinese and the US small and medium technology enterprises in terms of the four dimensions described above. In this section, academic literature on each of them is reviewed.


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Scientific institutions Role:

VCs

Reputation

- Suppliers of innovave ideas - Suppliers of top -talents - Suppliers of scienfic and technical experse

Role:

Collaboration in terms of Knowledge, toptalents, IP, spinoffs

- Business-experse - Financing in early-stage - networking Collaboration in terms of Investments; Business-expertise; Experts

Reputation

Collaboration in terms of knowledge, top-talents, IP,

demand for innovations

Small and Medium Innovation Enterprises Role: - The key source of technology innovaons.

Collaboration in terms of financing, support

Government


Role:

Industry (Suppliers, Competitors, Clients, other organizations) Role:

Figure 1. Conceptual framework

- Manufacturer of innovave products. - Generates demand for innovaons and Small science based enterprises/ startups

Reputation Reputation

Reputation

- Financing - Policy - Condions for all elements of ecosystem.

Collaboration in terms of materials, Intangible assets, Assistance

Infrastructure Role: - Creaon of favorable condions for the Small and Medium Innovaon Enterprises (technoparks , incubators, etc.) - Intermediate organizaons

3.1 The scale, diversity and the strength of entrepreneurial networks in China and the USA Research on network management has evolved over the last two decades. Small and medium technology enterprises network can be defined as a temporary constellation of partnering enterprises and other stakeholders that together develop distinct new products, processes and services (Rehm and Goel, 2017). Networks play a key role in the innovations. Business innovations can be co-created and coproduced only with other business partners (La Placa, 2014). The opportunity to collaborate and interact socially within a community of regional innovation system is positively associated with firm performance (Burrus, 2018). The research of Findik and Beyhan (2015) showed that external collaboration has positive and significant influence both perceptions associated with the product- and process-oriented impacts of innovation. Several types of research showed the significance of collaboration with the special stakeholders. For example, collaborations with customers, competitors, suppliers and universities enable the company to innovate because they are designed to provide both incentives and the mechanisms that facilitate the transfer, integration and creation of new knowledge between partners; that is, partners may help the company innovate because they provide knowledge the company needs to complement its own internal knowledge (Un and Rodríguez, 2017). Communication and social interaction between small and medium technology enterprises and the customers is the key to a successful product and service (Zulkepli et al., 2015). Collaborating with different research and development sources is one way in which firms can search for different types of knowledge for innovation (Hannigan et al., 2015). The research of technology companies of Iran showed that collaboration with research organizations and competitors have a positive effect on product innovation capability and the level of collaboration with different partners can enhance firms’ innovation capabilities only if the focal firm’s managers have developed the capacity to scan and acquire external knowledge (NajafiTavania et al., 2018). Cases of technology companies showed that networking helps to


refine and improve the overall business model (Oskam et al., 2018). La Rocca and Snehota (2014) concluded that innovation occurs only when business relationships are established and found that technological innovation is contingent on the development of business relationships, and that developing customer relationship is no less important than developing relationships with suppliers. However, it was found that at present, China was unable to establish long-term, stable cooperation relationship among China’s innovation actors such as government, research institutions, enterprises, universities and intermediaries (Zhao et al., 2015). On the other hand, Chinese entrepreneurs who possess political connections may also use these connections to gain performance advantages (Eesley et al., 2016). The analysis of 364 Chinese manufacturing, telecommunication and electronics companies showed that new product development performance is stronger under higher networking capability (finding, managing and leveraging networks ties) and higher networking ability (managers’ ability to successfully mingle and connect with the colleagues in the organization), i.e. a firm’s ability to realize the performance advantages fully depends on its networking capability and networking ability (Mu et al., 2017). In the USA, higher heterogeneity of knowledge sources (at the idea generation stage) will increase invention quality (Walsh et al., 2016). According to Zheng et al. (2014), the role of social network ties is found to be significant in crowdsourcing in China and the USA. All stakeholders in this research were classified on the base of Figure 1. 3.2 The quality of collaboration network Trustworthiness is one of the most important factors in social and economic interactions. Research on trust has been done in marketing, management, sociology and operations management areas (Swift and Hwang, 2013). According to the survey organized by the World Value Survey in 2014, which estimated interpersonal trust attitudes, showed that 62.69 per cent of Chinese respondents agreeing with the statement “most people can be trusted”, while in the USA, only 38.17 per cent agreed with that. Ke et al. (2015) figured out that different dimension of trust has different influence: affect-based trust (i.e. trust that encourages the willingness of members to consider others instead of exploiting others) has significant direct influence on performance, and an indirect influence on performance through cooperation; cognition-based trust (i.e. trust built on the confidence in partners’ competence) has no direct influence but has an indirect influence on performance through cooperation; system-based trust (i.e. good expectation for partners’ future action) has non-significant influence on performance. As compared with the USA, China is a society in which people place more importance on personal relationships (Zheng et al., 2014); in other words, the Chinese business culture is more human-hearted, based on respect and care. Guanxi is a critical factor in business success for Chinese business. The networks and connections developed by guanxi in Chinese society provide a special pathway to obtain unique resources and information for business to compete and create value in the marketplace. Berger et al. (2015) for their research use three variants of guanxi: ganqing (the emotional element in the formation of guanxi), rending (a co-native component of guanxi, level of human compassion and benevolence) and xinren (the length of mutual relationship, how business interactions are conducted and ways in which disputes are solved). Unlike Western business-to-business relationships, the Chinese guanxi approach is established and nurtured at an individual level. Chinese buyers have significantly lower perceptions of trust, commitment, communication and cooperation when they only have the modest guanxi with their supplier’s representatives (Yen and Abosag, 2016). High-tech manufacturing small and



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medium enterprises in China tend to build collaborative relationships with research institutions (Chung and Tan, 2016). The goal of this paper is to understand the collaboration quality network of which country is higher, i.e. which of two countries trust their stakeholders more and how they maintain relations. 3.3 Reputation in the sense of stakeholders’ perception at the local markets Reputation in the sense of stakeholders’ perception impacts stakeholder behavior and thus various stakeholder value drivers (for example, revenue, cost of capital, etc.). Reputations can differ among stakeholder groups (Gatzert, 2015). Entrepreneurial reputation is seen as a major determinant of credibility and influence in decision-making and in project implementation. Reputation is associated with trust and credibility and is considered essential for taking a position among the network at a given destination (Strobl and Peters, 2013). Reputation has the potential to attract customers and influence selling–buying processes. Agostini and Nosella (2016) showed that technological reputation played a central role in enhancing customer performance. They concluded that paying attention to the technical skill development of employees and encouraging a brand orientation mindset at work are critical to building a strong technological reputation. Reputation can also impact the behavior of suppliers and contractors or business partners (Raithel and Schwaiger, 2015). It was found that Innofund-backed firms in China generate significantly higher technological and commercialized innovation outputs as compared with their non-Innofundbacked counterparts and the same firms before winning the grant (Guo et al., 2016). All the informants from the Beijing companies agreed with the statement that maintaining good guanxi with the government was crucially important (Wu et al., 2016). The goal of this section is to understand, the small and medium technology enterprises of which country get more positive recognition from the stakeholders in the market. 3.4 Foreign network for the US and Chinese small and medium technology enterprises The rise in global networks through personal relationships has fueled an enormous increase (Cano-Kollmann, 2017). The survey results from Global Startup Ecosystem Report 2017 analyzing small technology companies showed that the Global Reach Index, based on the companies’ proportion of foreign customers for Beijing, is 20; for Silicon Valley, it is 9. Global Connectedness rate, measuring a technology company leader’s relationship with entrepreneurs in other countries, is 12 for Beijing and 1 for Silicon Valley. According to Child and Rodrigues (2015), a number of leading Chinese firms have begun to internationalize with a view to becoming global players in international markets. They are characterized by a more focused and longer-term strategic view, and appear to be developing the capacity to organize overseas operations systematically. Nordman and Tolstoy (2016) found that to convert opportunities conceived in international and home-market networks into innovative outcomes, small and medium technology enterprises need a relatively higher level of innovative collaboration in their partnerships with foreign market customers in comparison to when opportunities are conceived in the host-market network. Key foreign partnerships can facilitate interpretation and transfer of such opportunities to particular market settings so that firms become better equipped to develop innovative business solutions that are geared toward the customers’ preferences and requirements in a specific foreign market. At the same time, there are a limited number of literature sources about whether it is easy for the company to get access to the resources abroad such as information about the competitors, market demand, high-tech specialists and


financial support. It was shown that the Chinese returnee entrepreneurs have an international social network for their companies to develop an international network capability, which facilitate the international performance development (Bai et al., 2018). Some examples prove the importance of international networks. Finding ways to deepen economic cooperation between China and EU in joint innovation projects was found that global networks and collaboration are the best way to promote innovation (García-Herrero et al., 2017). The development of an international dimension for an agro-technology of small and medium Italian enterprises was recommended to strengthen relations with consolidators to be able to connect them with large foreign buyers (Caiazza, 2016). 4. Research methodology The current study uses a survey method to test the research in the four aspects described above. 4.1 Survey data To achieve research objectives, the authors developed questionnaire including five sections: (1) company profile; (2) domestic network and entrepreneurial resources evaluation; (3) collaboration with partners; (4) a degree of recognition in the market; and (5) foreign network. The questionnaires’ structure is presented in Table II. Company profile section involves questions on respondents’ company such as the year of the establishment, scientific area, fundraising process result, business abroad and several optional questions such as patents and employees number and revenue. For (B), (C) and (D) sections, multiple-choice answers were assigned to each question, including five-point scale (1 – very infrequent/totally disagree; 5 – very frequent/totally agree). The questionnaire was done in the Chinese language for the Chinese respondents and later was translated into English for the American respondents. The preparation of the questionnaire took from January 2016 until June 2016. 4.2 Data collection The test period began on June 2016 and finished on June 2017. 4.2.1 Data collection for Chinese companies. The channels for the questionnaire distribution included: direct paper distribution of the questionnaire; e-mail distribution (So jump platform was selected; all questions were mandatory, skipping or missing the answer were not allowed to be submitted); and Wechat link distribution (Wechat is the most popular communication platform in China, and has the option of creating surveys). The questionnaire was sent by email to Zhongguancun Software Park, Haidian Pioneer Park, Changping Biomedical Base, Daxing Biomedical Base, Wangjing Science and Technology Park and Haidian Venture Park.



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Table II. Questionaries’ structure

Section

Question purpose

Formulation question

Company profile

Identify general information about the company

Domestic network and entrepreneurial resources evaluation

Identify scale, diversity and the strength of entrepreneurial networks

Collaboration with partners

Identify how you would characterize the relationship

Degree of recognition in the market

Identify other key partnership and your company’s image

Foreign network

Identify the frequency of the communication with foreign stakeholders; identify if it is easy to get the access to the foreign resources

Year of establishment, scientific area, fundraising process result, business abroad and number of employees Estimate the number of stakeholders involved in business and fill in the frequency with which business associated with the individuals or organizations in country Complete trust for technical expertise, partners will never disclose trade secrets, partners provide the accurate information, always try to achieve win–win cooperation model, benefit both sides and continuous improvement, short-term sacrifices for longterm relationships and invest a lot of time and effort to maintain the relationship Employees proud to tell others that they are members of business, domestic competitors have great respect, domestic suppliers want to do business together, domestic customers highly evaluate products, local government highly appraises business, domestic investors are willing to contact with business, domestic media pays attention Rate the frequency of communication with non-US/Chinese stakeholders Company can easily obtain information about the company’s competitors abroad, market information, procurement, sales, management, technical knowledge and skills of foreign specialists, foreign scientific and technological support

On July 5, 2016, one of the authors was invited by the Overseas Chinese Affairs Office of the Beijing Municipal Government to attend the Zhongguancun Overseas Chinese Entrepreneurship conference. More than 500 distinguished experts in science and technology, and Chinese entrepreneurs from Beijing attended this conference. Sixty seven paper questionnaires were distributed during this event; however, because of the high mobility of the participants only eight questionnaires were collected. Personal connections (friends and family members) were used to help distribute the online questionnaire. Totally, 185 questionnaires were distributed and 87 (47 per cent) responses were received. All distributed questionnaires were in Chinese. 4.2.2 Data collection for the USA companies. The channels for the questionnaire distribution for American enterprises included: direct paper distribution, e-mail distribution (Google platform was selected; all questions were mandatory, skipping or missing the answer were not allowed to be submitted ).


One of the authors had studied at Singularity University (a private university based in Moffett Field, Silicon Valley) in 2011, and was included in the university group, which, until 2017, had over 1,000 people; most of them were entrepreneurs with companies in Silicon Valley. Therefore, this group was the key contact database for the online distribution questionnaire. The link to the survey was distributed among the participants. In total, 103 individuals from the group participated in the survey, and 47 completed questionnaires were received. Apart from that, since June 6 till June 11, 2017 the author participated in the conference in Santa Clara “Technology and Engineering Management Society” as well as visited relevant events with Silicon Valley entrepreneurs’ involvement. Totally 5 events were visited in Palo Alto, Santa Clara, Mountain View, San Francisco. The paper questionnaires were distributed among the participants. Thirteen completed questionnaires were received. Totally 60 responses were received. All distributed questionnaires were disclosed in English language. 4.3 Reliability and validity analysis of the questionnaire In this paper, IBM SPSS Statistics 22.0 software was used to test the reliability and validity. The results were based on the data from the respondents in Zhongguancun and Silicon Valley. The value of Cronbach’s alpha coefficients for the questions from scale, diversity and the strength of entrepreneurial networks (0.843), quality of collaboration network (0.89), reputation (0.906) and foreign network (0.927) sections are greater than the threshold value (0.7), indicating that the reliability is good fit. The Kaiser–Meyer–Olkin Measure (KMO) of sampling adequacy and Bartlett’s test of sphericity were carried out. The KMO value is 0.893, Bartlett’s test of sphericity was significant (significance value less than 0.005) and its value is 6,489.205. The factor coefficients of scale, diversity and the strength of entrepreneurial networks, quality of collaboration network, reputation and foreign network is greater than 0.5, indicating good validity. The diapason of factor coefficients’ value for 18 questions of scale, diversity and the strength of entrepreneurial networks section is from 0.593 to 0.71; for 7 questions of quality of collaboration network is from 0.57 to 0.64; for 7 questions of reputation is from 0.542 to 0.761, for 14 questions of foreign network section is from 0.529 to 0.838. 4.4 Respondents profile Sixty representatives from the US small and medium technology enterprises and 87 representatives from Chinese small and medium technology enterprises completed the survey. Most of the US companies are located in California (mainly, Silicon Valley). All Chinese companies are located in Beijing, in Zhongguancun. Respondents of the companies from both countries were founders or high-level managers (e.g. CEO, VP business development, COO, managing partner or marketing director). The technology fields of the companies include IT, biotechnology, energy, manufacturing and several minor areas such as space, robotics and new materials. The distribution of companies’ fields is represented in Figure 2. Most of the companies (94 per cent) participated in the survey were established after the year 2009. 45 per cent of the US companies and 31 per cent of Chinese companies have businesses abroad. 75 per cent of the US companies and 35 per cent of Chinese companies obtained investments from venture companies, other private investors and non-government foundations. 10 per cent of the US companies and 71 per cent of Chinese companies are


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Robocs 3%

USA

Manufacturing 19%

Space 3%

Biotech 30%

Energy 2%

IT 44%


Other 5%

China

New materials 2% Manufacturing 8% BioMedicine 25%

Figure 2. The distribution of companies’ fields

Energy 5% IT 55%

subsidized by the government foundations. All respondents from China had studied or worked abroad. 5. Results analysis ANOVA was applied to each question item to test the differences between the two group means, i.e. China and the USA. For the two samples, we compute F distribution. The critical point at a = 0.05 for F distribution with 1 degree of freedom for the numerator, and 145 degrees of freedom when the denominator is 3.91. The results, when F-value is greater than F critical and the p-value is smaller than 0.05, allows for rejecting the null-hypothesis (Aczel et al., 2012). 5.1 The scale, diversity and the strength of entrepreneurial networks in China and the USA The scale and diversity of entrepreneurial networks means that all respondents estimated the number of stakeholders (relatives or friends, suppliers, competitors, clients, government organizations, financial foundations, universities and research institutions, industrial organizations and accounting/law firms) involved in their business now (1 – means that the company does not have this stakeholder; 2 – means that the company has from 1 to 3 stakeholders; 3 – means that the company has from 4 to 7 stakeholders; 4 – means that the company has from 8 to 10 stakeholders; 5 – means that the company has more than 10 stakeholders); the strength of the entrepreneurial network includes the frequency of communication, estimated from 1 to 5 (1 – means that the communication with this stakeholder is very infrequent; 5 – means that the communication with this stakeholder is very frequent) with which the business associated with the individuals or organizations (stakeholders) in the country. We grouped the number of stakeholders involved in the business and the communication frequency with them because even if the company has any stakeholder, it is important to know how much and how often the company communicates with it. Table III summarizes the ANOVA results for each question item connected to scale, diversity and the strength of entrepreneurial networks.


Compared parameters of the Chinese and US companies

Mean China USA F-value

Personal The number of relatives or friends involved in business now

2.69

1.77

22.45*

Industry The number of suppliers involved in business now The number of competitors involved in business now The number of clients involved in business now The number of industrial organizations involved in business now

3.02 2.59 3.31 2.69

2.7 2.6 4.05 2.47

2.63 0.006 12.72* 1.09

2.56

1.78

20.13*

2.64

2.4

1.68

2.95

1.97

30.28*

Infrastructure The number of accounting/law firms involved in business now

2.54

1.95

15.4*

Personal Collaboration frequency with relatives or friends

3.08

1.95 30*

Industry Collaboration frequency with suppliers Collaboration frequency with competitors Collaboration frequency with clients Collaboration frequency with industrial organizations

3.47 2.93 3.67 3.28

2.93 1.76 4.27 3.08

6.98* 43.66* 11.95* 0.85

Government Collaboration frequency with government organizations

3.14

2.59

6.83

3.12

3.28

0.52

Government The number of Government organizations involved in business now Financial foundations The number of financial foundations (VCs, investors or business-angels) involved in business now Scientific institutions The number of universities and research institutions involved in business now

Financial foundations Collaboration frequency with financial foundations (VCs, investors and business-angels) Scientific institutions Collaboration frequency with universities and research institutions

3.43

2.8

8.65*

Infrastructure Collaboration frequency with accounting/law firms

3.13

2.2

26.12*

Notes: *p < 0.01; **p < 0.05

Regarding the results, most of the American companies prefer to work with the limited number of people who are their friends or family members (according to the results, the most of the companies have 1-3 friends or family members, or do not have any at all in absolute value), while Chinese companies have more friends and family members involved in the activity of the organization. Moreover, the collaboration frequency with personal stakeholders in Chinese companies is much higher than in the USA. These differences were all highly statistically significant F = 22.45 (the third biggest value) and F = 30 (the second


Table III. Differences in scale, diversity and the strength of entrepreneurial networks: China vs USA


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biggest value); p < 0.01. Therefore, Chinese small and medium technology enterprises involve more personal stakeholders (like friends and family members) in the activities of the company and collaborate with them more than the companies in the USA. Analyzing the results for industry stakeholders, as compared to the Chinese companies, American companies worry more about the clients and try to have more communication with them (the highest-scored 4.05 on a five-point scale). Therefore, the US’s small and medium technology enterprises involve more clients, and the collaboration with the competitors are more frequent at the American companies. Collaboration frequency with suppliers and competitors has more Chinese companies rather than the US ones and these differences are significant F = 6.98, F = 43.66 (the biggest value); p < 0.01. The number of suppliers is more in Chinese companies and the difference is not statistically significant ( p > 0.05). Chinese companies have more the number of competitors and industrial firms as well as the Collaboration frequency with Industrial organizations than the USA but it was not statistically significant. The number of government organizations involved in the activities of Chinese companies (M = 2.56) is greater than that involved in the activities of the US companies (M = 1.78). This difference is significant ( p < 0.05). Regarding the communication frequency with government organizations, it is more intensive among Chinese organizations (M = 3.14) than among the USA companies (M = 2.59). This difference is significant on the basis of F = 6.83; p < 0.05. According to the analysis of financial foundation, its number involved in the activities of Chinese companies (M = 2.64) is more than in the USA companies (M = 2.4). The difference is not significant because p > 0.05. The collaboration frequency with a financial organization was found to be more among the USA companies (M = 3.28) than among the Chinese (M = 3.12), but this difference was not statistically significant. The number of scientific institutions involved in the activities of Chinese companies (M = 2.95) is greater than the number of scientific institutions involved in the activities of the US companies (M = 1.97). This difference is statistically significant ( p < 0.05). Regarding the communication frequency with scientific institutions, it is more intensive among the Chinese organizations (M = 3.43) than among the US companies (M = 2.8). This difference is significant on the base of F = 8.65; p < 0.05. Therefore, Chinese small and medium technology enterprises involve more scientific institutions in the activities of the company and collaborate more frequently with them than the companies in the USA. The number of accounting, law and other support organizations working with Chinese companies is more than with the US companies. Both differences are statistically significant. 5.2 The quality of collaboration network All responders characterize the relationship with their partners; the results are estimated from 1 to 5 (1 – means totally disagree; 2 – means do not agree; 3 – means neutral; 4 – means agree more; 5 – means fully agree). Table IV summarizes the ANOVA results for each question item connected to the quality of collaboration network. According to the results, the quality of collaboration network in the USA is higher than in China. The only factor Belief that the partners will never disclose our trade secrets did not show the difference significance of results. The rest factors’ difference is statistically significant. All the ratings showed very high results for the questions regarding the quality of collaboration network. The means for both countries were mostly ranging between 3 and 5,


with 5 being the maximum. The parameter Together always trying to achieve win–win cooperation model has the biggest meaning for China (M = 3.75) and the US companies (M = 4.3) among the remaining parameters. 5.3 Reputation in the sense of stakeholders’ perception at the local markets All responders characterize the Degree of their reputation in the market; the results are estimated from 1 to 5 (1 – means totally disagree; 2 – means do not agree; 3 – means neutral; 4 – means agree more; 5 – means fully agree). Table V summarizes the ANOVA results for each question item connected to the Degree of recognition in the markets of China and the USA. According to the results, employees of the US companies are prouder to tell others that they are members of the business (the biggest mean value M = 4.37 and the difference is statistically significant) than those in the Chinese companies (M = 3.56). Also, domestic customers of American companies positively rate the business products (M = 4.12) more than the domestic customers in China. The domestic media gives more positive coverage for the American companies than for Chinese, but this difference is not statistically significant. Chinese domestic competitors respect the business of the local companies more than the American competitors, but the difference is not very big (M = 3.59 and M = 3.5, respectively); moreover, the difference is not statistically significant.


Mean Compared parameters of the Chinese and US companies Full trust for technical expertise Belief that the partners will never disclose our trade secrets Trust that our partners provide the accurate information Together always trying to achieve win–win cooperation model Willing to benefit from both sides and continuous improvement Ability to make short-term sacrifices for long-term relationships Invest a lot of time and effort to maintain the relationship

China

USA

F-value

3.54 3.44 3.55 3.75 3.25 2.9 3.17

4 3.6 3.9 4.3 4.3 4 4.02

9.1* 0.84 5.34** 14.72* Table IV. 35.95* Differences in quality 29.06* of collaboration 25.96*

network: China vs USA

Notes: *p < 0.01; **p < 0.05

Mean Compared parameters of the Chinese and US companies Employees proud to tell others that they are members of the business Domestic competitors respect for your company Domestic suppliers want to do business with your company Domestic customers positively rate your business products The local government highly appraises your business Domestic investors are willing to work with your business The domestic media gives positive coverage of the business Notes: *p < 0.01; **p < 0.05

China

USA

F-value

3.56 3.59 3.77 3.71 3.68 3.8 3.45

4.37 3.5 3.55 4.12 3.23 3.48 3.65

26.52* 0.29 2 7.25* 6.8** 3.73 1.27

Table V. Differences in reputation in the sense of stakeholders’ perception at the local markets: China vs USA

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Chinese domestic suppliers appreciate doing business with the local companies more than the US domestic suppliers with the US companies (M = 3.77 and M = 3.55, respectively). The difference is not statistically significant. The Chinese Government appraises local Chinese companies more than the US Government appraises local US companies. And Chinese domestic investors are more inspired to work with the Chinese companies as compared to the US investors with the US companies. These two differences are not very big, but the differences are statistically significant.


5.4 Foreign network for the US and Chinese small and medium technology enterprises The strength of the foreign network includes the frequency of communication, estimated from 1 to 5 (1 – means very infrequent; 2 – means infrequent; 3 – means from time to time; 4 – means frequent; 5 – means very frequent) with which the business associated with the individuals or organizations (stakeholders) in another country (not in China for Chinese companies and not in the USA for the US companies). Table VI summarizes the ANOVA results for each question item connected to the strength of foreign networks. According to the results, Chinese companies collaborate more with the foreign stakeholders than the US companies. The only factor Collaboration frequency with clients abroad did not show the different significance of results. The rest factors’ difference is statistically significant. The Access to foreign resources estimated from 1 to 5 (1 – means totally disagree; 2 – means do not agree; 3 – means neutral; 4 – means agree more; 5 – means fully agree) with which the business can get access from another country (not in China for Chinese companies and not in the USA for the US companies).

Compared parameters of the Chinese and US companies

F-value

Personal Collaboration frequency with relatives or friends

3.1

1.53

68.61*

Industry Collaboration frequency with suppliers Collaboration frequency with competitors Collaboration frequency with clients Collaboration frequency with industrial organizations

3.28 3 3.45 3.26

1.92 1.43 3.37 2.2

45.78* 87.07* 0.14 24.96*

Government Collaboration frequency with Government organizations

3.08

1.7

48.6*

3.29

2.45

Scientific institutions Collaboration frequency with universities and research institutions

3.41

1.92

49.8*

Infrastructure Collaboration frequency with accounting/law firms

3.18

1.32

139.21*

Financial foundations Collaboration frequency with financial foundations (VCs, investors and business-angels)

Table VI. Differences in strength with the foreign networks: China vs USA

Mean China USA

Notes: *p < 0.01; **p < 0.05

9.67*


Table VII summarizes the ANOVA results for each question item connected to the Access to foreign resources. On the basis of the results, the Chinese companies can get access to the foreign resources more easily in the USA. The only factor Information about company’s competitors abroad did not show the different significance of results. The remaining factors’ difference is statistically significant. The means for the results of Chinese companies indicate that the Chinese companies agree or stay neutral for getting easy access to foreign resources, while the US companies do not agree or stay neutral about getting easy access to foreign resources. The parameter Scientific and technological support, which the company can easily get from abroad has the biggest meaning for China (M = 3.7); for the US companies, the biggest is Market demand information, which the companies can get easily abroad (M = 2.93).


6. Conclusion & implication The purpose of this paper was to make a comprehensive comparison between the Chinese and US small and medium technology enterprises in the following aspects of their activities: scale, diversity and the strength of entrepreneurial networks, quality of collaboration network, reputation in the sense of stakeholders’ perception at the local markets and foreign network. The data from the survey were used. To analyze the research data, t-tests were also done. An analysis of stakeholders’ networks provides a framework for understanding how resources and knowledge are collected, managed and applied. Results showed that Chinese companies involve in its activities and collaborate more with stakeholders such as friends and family members, government, universities, intermediate organizations (accounting and law) more than in the USA companies. The only stakeholder that the USA companies have more than Chinese and collaborate more is the clients. Moreover, it also found that customers in the USA positively rate the local products. So, as compared to Chinese companies, the US companies place more value to the cooperation with domestic clients as the main source of revenue, and these clients relate well to local production. The number of venture companies and other private investors involved in the activities of Chinese companies is the same as in the US companies; the collaboration intensity has no difference with the US companies. However, the results showed that Chinese domestic investors are more inspired to work with the Chinese companies. On the other hand, the number of companies that participated in the survey and got the investments is more in the USA and not in China. It could be concluded that the quality of negotiations is higher in the US companies and that the number of private investors, who

Compared parameters of the Chinese and US companies The company can easily get access to: Information about the company’s competitors abroad Market demand information abroad Procurement, sales, management and other information Technical knowledge and skills of foreign specialists Foreign scientific and technological support Notes: *p < 0.01; **p < 0.05

Mean China USA 3.43 3.55 3.63 3.66 3.7

3.13 2.93 2.57 2.88 2.82

F-value 2.22 8.78* 26.17* 16.41* 17.85*

Table VII. Access to foreign resources: China vs USA


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are ready to invest now are more in the USA. To answer this question and arrive at correct conclusions, it is necessary to conduct in-depth interviews with companies as well as private investors. It was found that as compared to those in the Chinese companies, the quality of collaboration network in the US companies – including trusting technical expertise and accurate information, achieving win–win cooperation, benefiting both sides, the ability to make sacrifices and investing time in a business relationship – is higher. Both countries showed the best result in the parameter connected with achieving win–win cooperation. It was found that the employees of the American companies were prouder to tell others that they are members of the business rather than those in the Chinese companies. The Chinese Government also tended to appraise local Chinese companies more. Although it was found by Ali et al. (2015) that the relation between company reputation and its stakeholders depends on the country of the study, the comparison of the US and Chinese small and medium technology enterprises showed that competitors, suppliers, investors and media share the same relation with the companies in both countries. Although Liefner et al. (2006) concluded that not all of the high-tech companies in Zhongguancun are able to make use of international linkages in the innovation process as about half of them do not have the necessary capabilities, it was found that Chinese companies can get access to foreign resources more easily than the USA companies do. It should be taken into account that all respondents spent several years abroad mainly in Europe and the USA for either studying or working. Living in the foreign environment positively affected the ability to collaborate with foreign partners and make valuable connections, therefore increasing the value of the company. On the other hand, if the Chinese entrepreneurs spent a long time abroad he/she risked losing the local contacts, which are considered far more important for the Chinese environment because of the guanxi concept. Therefore, it is very important for Chinese entrepreneurs to find a balance between having a chance to get the experience abroad and keep in touch with the business network in China. It provides useful information to policymakers to discuss key elements related to the most appropriate policy to connect with future Chinese entrepreneurs who live abroad. Table VIII summarizes the results found from the research. The results can be useful for Chinese and American entrepreneurs wishing to enter American and Chinese markets. Many American firms view participation in China’s market as critical to their global competitiveness, while Chinese firm prefer to play a significant role in the US market. For example, according to China–US trade issues, the total US–China merchandise trade rose from $2 billion in 1979 (when China’s economic reforms began) to $636 billion in 2017. This study will help companies from both countries to see the differences and similarities of the two regions and adapt their activities and behaviors according to the specifics of these regions and local environments. Some theoretical contributions were also done. On the above shown classification of stakeholders, we displayed the communication frequency between small and medium technology enterprises and its stakeholders as well as the number of stakeholders involved in day-to-day activities of the enterprises. While previous research explores challenges that firms face owing to the market, Government and institutional issues, we contribute to the understanding of other collaboration factors while contributing to the parameters and definitions such as scale, diversity, the strength of entrepreneurial networks in China and the USA, quality of collaboration network, reputation in the sense of stakeholders’ perception at the local markets


Parameters

Differences

Similarities

The scale, diversity and the strength of entrepreneurial networks

Chinese companies have more stakeholders and collaboration more with relatives and friends, Government, universities and accounting/law Chinese companies collaborate more with competitors and suppliers The US companies have more stakeholders and more collaboration with clients The US companies have more trust in their partners’ technical expertise, accurate information, achieving win–win cooperation, benefit from both sides, ability to make sacrifices and invest time in business relationship Chinese companies The local government appraises business US companies Employees are prouder to tell others that they are members of the business Domestic customers positively rate your business products Chinese companies have better access to foreign resources and more collaboration with relatives or friends, suppliers, competitors, industrial organizations, Government organizations, financial foundations, universities, and accounting/law firms

Both have the same number of stakeholders among Financial foundations, Industrial organizations, Competitors, Suppliers Both have the same level of collaboration frequency with industrial organizations and financial foundations

The quality of collaboration network

Reputation in the sense of stakeholders’ perception at the local markets

Foreign network for the US and Chinese small and medium enterprises


Both believe that the partners will never disclose their trade secrets

For both Domestic competitors show respect for company, Suppliers want to do business with company, Domestic investors are willing to work with business, The domestic media gives positive coverage of the business Both have the same level of collaboration frequency with Table VIII. clients Differences and Both can easily get the access to similarities of the information about the company’s Chinese and US small competitors abroad

and foreign network for the US and Chinese small and medium technology enterprises. It provided the empirical study of these factors. Do we contribute to the literature by asking the following question: Is it easy or not for the company to get the access to the resources abroad? To measure the connectedness rate, i.e. technology company leader’s relationships with entrepreneurs in other countries, it is important to take into account the company itself and the team members’ previous experiences. If the top-managers and cofounders had previous experience abroad, they are well-prepared to play in the international arena. It is the first study of its kind, which compares Chinese and American small and medium technology enterprises across four key domains. This paper allowed achieving some results about Zhongguancun and Silicon Valley. However, every country and every region shows particular characteristics; therefore, further research can be done to replicate in other geographic areas.

and medium enterprises


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About the authors Anna Trunina is a Doctoral Candidate in the School of Economics and Management, University of Chinese Academy of Sciences, China. She previously got a Master’s degree in Mechanical Engineering, Bauman Moscow State Technical University in Russia, graduated from Singularity University, Silicon Valley, USA and has over five years of working experience in Russian and the US innovation environments. Her research interests are innovation management, emerging industries, collaborative networks and innovations in Asia. Anna Trunina is the corresponding author and can be contacted at: [email protected]. Dr. Xielin Liu is a Professor in the School of Economics and Management, University of Chinese Academy of Sciences, China. His research interests are mainly on innovation management. He has published well over 50 articles in major refereed journals in business and management such as Research Policy, Technovation and the International Journal of Technology Management. Dr. Jian Chen is an Assistant Researcher at the Chinese Academy of Science and Technology for Development, Ministry of Science and Technology. Her research interests are innovation ecosystem for industrial development, innovation policies in China and entrepreneurship management. She obtained her PhD in innovation management from the University of Chinese Academy of Sciences. She has published several articles in International Journal of Technology Management and other journals in technology and innovation management.

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