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The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

The purpose of this paper is to investigate how institutional voids influence high‐tech ventures' innovation, and what strategies high‐tech entrepreneurs deploy to cope with the institutional environments they encounter.

A qualitative research approach was taken. In‐depth interviews were conducted with nine high‐tech entrepreneurs. In addition, governmental officials, overseas associations, and professional investors were interviewed for more/further observations.

Institutional voids may negatively influence high‐tech ventures' innovation. They might be moderated by guanxi and government active involvement. On the contrary, institutional voids can offer high‐tech entrepreneurs the opportunity to create innovative business models. The co‐evolution of institutional developments and high‐tech ventures illustrates the particular characteristics of Chinese entrepreneurial environment.

Qualitative study cannot simply be generalized, albeit this explorative study provides illustrative insights. Quantitative research (e.g. surveys), which is applied to test the propositions, calls for further scholarly inquiry.

Overseas entrepreneurs are presented with the opportunities to pursue an entrepreneurial career. SMEs from developed economies may join the movement with technology entrepreneurs to enter the Chinese market and co‐shape the market development.

Institutional voids were conceptualized from a multi‐dimensional perspective, namely national, regional, and individual. By providing qualitative evidence, different mechanisms to fill the institutional voids are explored.

The purpose of this study is to identify the types and features of business relationship when the value co-creation phenomenon is extended to an early stage of the value chain, in which technological innovation is essential, in a high-tech business-to-business (B2B) market.

The methodology of building a theory from a case study is adopted in this study to propose an early-stage value co-creation network. Qualitative data are coded on the basis of grounded theory coding after collecting the triangulation data from multiple sources.

In a high-tech B2B market, three types of business relationships (supplier–customer mutual, supplier-centric and network-based business relationships) co-create values at an early stage of the value chain. Intellectual resource, efficiency resource and supplier-centric business relationships are uniquely found in this stage.

This study provides new insight suggesting that the notion of value co-creation can be extended to early stages of the value chain in a high-tech B2B market. In addition, this research identifies vital business relationships and how these relationships develop successfully at an early-stage value co-creation network in a high-tech B2B market.

Technology development managers at an early stage of the value chain can co-create relationship benefits by building proposed business relationships integrating resources in a high-tech B2B market. In addition, marketing managers should consider the early stage as another source of value co-creation.

The notion of value co-creation is extended from the later stage to an early stage of the value chain in a high-tech B2B market. Consolidated framework of a value co-creation network integrating actors, resources and relationships, suggested in this study, will be valuable for further theoretical research and business application.

The purpose of this paper is to determine if the relationship between growth and research and development (R&D) intensity is of a different nature in the context of low‐ and high‐tech Portuguese service small to medium‐sized enterprises (SMEs).

The System Analysis of Iberian Balance Sheets database is used. Based on the European Union's recommendation, L124/36 (2003/261/CE), the authors select 764 low‐tech and 139 high‐tech Portuguese service SMEs for the period 1999‐2006. As method of analysis, panel data are used.

A negative relationship between growth and R&D intensity for low‐tech Portuguese service SMEs is identified, whatever the level of R&D intensity. For high‐tech Portuguese service SMEs, a quadratic U‐shaped relationship between growth and R&D intensity is identified. Moreover, the authors find that relationships between growth and determinants are of a special nature in the context of high‐tech Portuguese service SMEs with high levels of R&D intensity.

It is recommended that as far as possible the managers/owners of low‐tech Portuguese service SMEs, and especially high‐tech ones with non‐high levels of R&D intensity, hire qualified human resources and make more continuous investment in R&D. The authors advise managers/owners of high‐tech Portuguese service SMEs with high levels of R&D intensity to establish stable relationships with creditors. Policy‐makers should increase financial support directed, above all, to innovative Portuguese service SMEs.

The paper is pioneering in presenting different relationships between growth and R&D intensity in the context of low‐ and high‐tech service SMEs.

The purpose of this paper is to explore and compare the extent of intellectual capital (IC) and its four components in high-tech and non-high-tech small and medium-sized enterprises (SMEs) operating in China’s manufacturing sector, and to examine the relationship between IC and the performance of high-tech and non-high-tech SMEs.

The study uses the data of 116 high-tech SMEs and 380 non-high-tech SMEs listed on the Shenzhen stock exchanges during 2012–2016. The modified value added intellectual coefficient (MVAIC) model is used incorporating four components, namely, capital employed, human capital, structural capital and relational capital. Finally, multiple regression analysis is utilized to test the proposed research hypotheses.

The findings of this paper reveal that there is significant difference in MVAIC between high-tech and non-high-tech SMEs. The results further indicate a positive relationship between IC and financial performance of high-tech and non-high-tech SMEs. Specifically, IC is positively associated with firms’ earnings, profitability and operating efficiency. Additionally, capital employed efficiency, human capital efficiency and structural capital efficiency are found to be the most influential value drivers for the performance of two types of SMEs while relational capital efficiency possesses less importance.

This paper will provide a valuable framework for executives, managers and policy makers in managing IC within the Chinese context.

To the best knowledge of the authors, this is the first empirical study that has been conducted on high-tech and non-high-tech SMEs in the manufacturing sector in China.

This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively.

This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries.

The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model.

Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit.

Though certain characteristics of micro-firms affect the likelihood of their participation in external relationships, how cooperation in craft enterprises differs from low and high-tech enterprises has not been investigated yet. Therefore, this study aims to fill the above gap in the literature.

This study adopts a descriptive approach by extensively reviewing relevant literature to explore the unique characteristics and nature of micro-firm's co-operative behavior. The theoretical approach of this research is grounded in resource-based view and dynamic capabilities theories.

This study finds that handicraft micro-firms possess special and unique characteristics that differentiate them from low- and high-tech firms. Further, handicraft micro-firms' co-operative behavior also differs from other firms in terms of cooperation motives, breadth, depth and factors that inhibit or promote cooperation. Additionally, in small handicraft firms, the co-operation is more informal, personal and through social networks, whereas in the corporate sector, it is more formal, direct and through supply chains. This study also argues that contrary to handicraft and low-tech firms, high-tech firms are more likely to cooperate with external partners and invest heavily in R&D for new product development (often radical in nature).

This study enriches our understanding of handicraft micro-firms' special and unique characteristics that differentiate them from low- and high-tech micro-firms. This research also provides in-depth knowledge to understand the handicraft micro-firms’ co-operative behavior and how it differs from low- and high-tech firms.

High‐tech industry transferring shows different features to the transferring of the traditional industries. In order to explain those special features in China, the purpose of this paper is to build a new conceptual model for high‐tech industry transferring and explore some empirical evidence.

This paper employs a perspective of specialization to analyze high‐tech industry transferring and a primary conceptual analytical model is discussed. Key models and methodologies are the industrial gravity center model, dynamic modes analysis, character induction and mechanism deduction method.

The features of high‐tech industry transferring within the China context include fast, surge, inverse‐gradient, as well as agglomeration and specification transferring. Based on the transfer pattern, high‐tech industry transferring modes are classified into two categories: vibration transferring and surge transferring.

Using a conceptual model, this paper analyzes the features of high‐tech industry transferring in China and proposes two typical patterns to explain how the industries transfer and what are the dynamic mechanisms. In order to improve high‐tech industry transferring in China, five policy implications are recommended.

The extant literature on initial public offerings (IPOs) generally assumes that a high degree of pre‐IPO leverage serves as a positive signal of firm quality as it forces a firm's managers to adhere to tough budget constraints. The purpose of this paper is to question the validity of this assumption when it is indiscriminately applied to all firms, while other potentially important determinants of a firm's optimal capital structure are ignored. High‐tech versus low‐tech firms are specifically focused on.

Multivariate regression controlling is used for various firm and offer characteristics, market and industry returns, and potential endogeneity between investment bank rankings, price revisions, and under‐pricing.

It is found that debt only serves as a signal of better firm quality for low‐tech IPOs, as reflected in smaller price revisions and lower under‐pricing. For high‐tech IPOs, the effect of leverage is reversed: for these firms, higher leverage is associated with increased risk and uncertainty as reflected by higher price revisions and greater under‐pricing. The results remain significant after controlling for various firm variables as mentioned above.

The research results allow managers of high‐tech firms that contemplate going public to better understand the effect their company's capital structure will have on the pricing of their IPO. Prior research generally suggests that – irrespective of a firm's underlying characteristics – higher financial leverage results in lower under‐pricing. The findings highlight the falsity of this generalization and point out that it only holds for low‐tech firms. Firms that operate in a high‐tech sector, on the other hand, will leave less money on the table if they use equity rather than debt financing.

It is shown that leverage only serves as a positive signal for low‐tech firms. The IPOs of these firms generally undergo smaller price revisions and are less under‐priced than the IPOs of low‐tech firms that use little debt in their capital structure. While this result is consistent with earlier studies, it is show that the relationship between these variables reverses for high‐tech IPOs. Specifically, it is found that high‐tech IPOs with high leverage undergo larger price revisions and are more under‐priced than high‐tech firms with low leverage. In contrast to earlier findings, this suggests that for high‐tech IPOs, higher leverage implies increased ex‐ante uncertainty and risks.

This paper aims to identify the influence of innovation network and technological learning on innovation performance of high-tech cluster enterprises.

Using a questionnaire, data are collected from Dalian High-tech Industrial park in China. In addition, structural equation model is used to identify the influence of innovation network and technological learning on the innovation performance of high-tech cluster enterprise.

The findings of this study show that the centrality of network location and the strength of the network relationship have a direct positive effect on technology acquisition, technology digestion and technology exploit of high-tech cluster enterprises. Meanwhile, technology acquisition has a direct positive effect on technology digestion, technology digestion has a direct positive effect technology exploit, and technology exploit has a direct positive effect innovation performance of high-tech cluster enterprises.

To improve innovation performance, high-tech cluster enterprises should not only nurture and optimize innovation networks but also improve technological learning ability.

This paper empirically supports the significant influence of innovation network and technological learning on innovation performance. While the results provide guidance for researchers and practitioners, it also adds value to innovation-related research.