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The purpose of this paper is to study the operational competitiveness and identify the development route of Chinese high‐tech manufacturing companies by comparing with other similar international manufacturing companies of global manufacturing strategies database.

The preliminary analytical models for competitiveness analysis are used to analyze the operational competitiveness strategies in three different types of Chinese high‐tech manufacturing companies based on the weights of the multi‐criteria manufacturing strategies, which are calculated using analytic hierarchy process method. Benchmarking between case companies and leading companies of prospector, analyzer and defender groups is applied to evaluate the manufacturing strategies further.

As a result of the case studies, it is possible to understand operational competitiveness manufacturing strategies for the case companies, to show one development route for Chinese high‐tech manufacturing companies to be competitive in their markets.

Chinese high‐tech manufacturing companies have their own operational strategies in different development phase. The different weights of important factors such as quality, cost, time and flexibility make the case companies to have some advantages in prospector, analyzer and defender. The preliminary analytical models are effective for Chinese high‐tech manufacturing companies to calculate their operational competitiveness under the influence of Chinese culture and macro‐control.

Benchmarking of operational competitiveness is presented to evaluate the manufacturing strategies in this paper. One development route of Chinese high‐tech manufacturing companies, which is under the influence of Chinese culture and macro‐control, is promoted.

The purpose of this paper is to examine the effects of parameter uncertainty in the returns process with regime shifts on optimal portfolio choice over the long run for a static buy-and-hold investor who is investing in industry portfolios.

This paper uses a Markov switching model to model returns on industry portfolios and propose a Gibbs sampling approach to take into account parameter uncertainty. This paper compares the results with a linear benchmark model and estimates without taking into account parameter uncertainty. This paper also checks the predictive power of additional predictive variables.

Incorporating parameter uncertainty and taking into account the possible regime shifts in the returns process, this paper finds that such investors can allocate less in the long run to stocks. This holds true for both the NASDAQ portfolio and the individual high tech and manufacturing industry portfolios. Along with regime switching returns, this paper examines dividend yields and Treasury bill rates as potential predictor variables, and conclude that their predictive effect is minimal: the allocation to stocks in the long run is still generally smaller.

Studying the effect of regime switching behavior in returns on the optimal portfolio choice with parameter uncertainty is our main contribution.

The purpose of this paper is to examine the impact of intellectual capital (IC) and its components (human, structural and relational capitals) on the performance of manufacturing listed companies in China. This paper also investigates the impacts of company ownership, industry attributes and region on the IC-performance relationship.

The study uses the data of 953 manufacturing companies listed on the Shanghai and Shenzhen Stock Exchanges over the period 2012–2016. The modified value-added intellectual coefficient (MVAIC) model is applied to measure IC efficiency. Finally, multiple regression analysis is employed to test the research hypotheses.

This study reveals that IC can enhance firm performance in China's manufacturing sector. Overall, earnings are affected by physical capital, human capital (HC) and structural capital (SC), and profitability and productivity are influenced by physical capital, HC, SC and relational capital. Physical capital is the most influential contributor to firm performance. In addition, state-owned enterprises have a greater impact of IC on firm performance than private-owned enterprises; high-tech manufacturing companies have higher IC performance than non-high-tech manufacturing companies; manufacturing companies in China's eastern region have higher IC performance than the counterparts in central and western regions.

The findings may help managers, stakeholders and policymakers in developing countries to effectively and efficiently manage their IC resources.

This is the first study to evaluate IC and its relationship with firm performance among Chinese manufacturing listed companies using the MVAIC model.

This paper empirically explored the influence of external and internal factors on technological and non-technological innovation of 5747 Indian firms. The study also explored novel insights about manufacturing firms by segregating them into high-technology and low-technology industries.

The study employed hierarchical regression analysis to analyse a cross-sectional dataset gathered from the World Bank enterprise survey. The firms are segregated into high-technology and low-technology industries based on the technology-intensity classification of the manufacturing industry given by the Organisation for Economic Co-operation and Development.

The main results highlight that technological and non-technological innovation was primarily driven by internal resources and capabilities rather than external factors. The authors found the highest effect of research and development spending on both forms of innovation. In both high-tech and low-tech industries, technology transfer is positively associated with technological innovation and negatively associated with non-technological innovation. Furthermore, external business support has substantially influenced non-technological innovation in low-tech industries.

This study used two-step hierarchical regression to explore the influence of external and internal factors on technological and non-technological innovation separately. Exploring determinants of innovation in high-technology and low-technology industries also brings the distinct prerequisites of enhancing innovation to the attention of policymakers and industry experts.

This study aims to explore the strategic impact of R&D and export activity on the diverse dimensions of US manufacturing firms’ performance. It also explores, using a predictive analytic model, the interactive synergistic effect that R&D and exports have on firm performance.

This study presents an innovative two-stage regression-neural network approach. Complementing conventional statistical analysis, the predictive backpropagation neural network explores the relative impact of R&D and exports and their synergistic effect on firm performance.

This study demonstrates the significant and positive effect of R&D and export strategy/activity on the economic performance of leading US manufacturing firms, particularly on their market-based performance (i.e. sustained growth rate or SGR). Furthermore, this study finds that the synergistic effect of R&D and exports on short-term performance (i.e. return on investment) is positive in high-tech firms but negative in low-tech firms. However, the synergistic effect on SGR is increasingly positive regardless of the level of technology.

In addition to traditional statistical analysis, this study uniquely investigates the relative importance of selected strategic variables, along with R&D and export activity and their differential synergistic effects, for firms’ economic performance in contrasting industry settings (high-tech vs low-tech).

This paper aims to examine whether foreign technology acquisition is complementary to internal technology development in the context of a developing country.

The selection model developed by Heckman (1979) was applied with the balanced panel data of manufacturing enterprises from the Annual Enterprise and Technology Surveys from 2012 to 2016 conducted by the Vietnamese General Statistics Organization.

The results indicate that foreign technology acquisition and internal technology development are complementary innovation options. Particularly, the number of patents granted for manufacturing enterprises positively affects the probability that enterprises acquire foreign technologies. This effect is stronger in cases of high-tech industries than in cases of low-tech industries.

Regarding the relationship between internal technology development and foreign technology acquisition, the findings suggest that adoption of foreign technology acquisition and priority in budget allocation for foreign technology acquisition are different in nature and that budget allocation is a more complex issue and may depend on other factors.

For developing countries, governments should adopt policies supporting domestic enterprises in acquiring technologies from advanced countries that could complement the locally developed technologies. These supports should focus on the high-tech or high-innovation rate industries.

In the context of a developing economy, the complementary effect of internal technology development and foreign technology acquisition is stronger in cases of the high-tech industries than in cases of the low-tech industries.

The purpose of this paper is to disclose the commonalities and differences among business owners of technology‐based firms in Germany. The paper addresses both single entrepreneurs as well as entrepreneurial teams regarding gender.

The paper examines firm characteristics and firm success variables in light of gender. Data were sourced from 593 firms in very‐high‐tech‐manufacturing, 886 firms in high‐tech manufacturing, and 4.822 firms in technology‐based service industries.

Results confirm the supposed gender gap in the technology industry. Whereas firm characteristics such as firm size, number of employees, and revenues are correlated to gender, firm success appears to be independent of these.

This paper focuses on the analysis of firm characteristics and gender variables. Due to the data sample, it contributes to the understanding of gender, as well as firm success and characteristics of German technology‐based firms.

The quantitative nature of this study contributes to reducing the scarcity of existing studies in the field of women entrepreneurship in technology‐based industries in Germany. It offers insights into the gender and entrepreneurial team characteristics of these firms.

In recent years there has been a shift towards the inclusion of agile processes in the development of manufacturing strategies. This work explores the agility of operations in four SMEs in high‐tech manufacturing and the impact made by information systems to agile performance in those companies. The study demonstrated that information systems are relegated behind other enablers of agility. Although information systems are often used to support agility, information systems in themselves are not sufficient to achieve agility in business processes. Furthermore, the case studies demonstrate that companies rely upon non‐IT attributes to improve the agility of their manufacturing operations. The results of the study suggest that information systems play a more significant role for enhancing agility.

The importance of supply chain network centrality has been widely recognized in the manufacturing literature. This study extends this literature by investigating the relationship between network centrality and innovation value. “Innovation value” refers to an innovation's impact, quality and potential future contribution to technological development in a business community. This study also aims to examine whether the relationship between supplier centrality and innovation value is contingent upon supplier acquisition.

The study hypotheses are tested with archival data collected from US high-tech manufacturing industries over the 17-year period. Negative binomial regression analysis was used to test the hypotheses.

The authors found that supplier centrality has a significant positive relationship with innovation value. Moreover, an increase in supplier acquisition activities makes the relationship between supplier centrality and innovation value more positive.

This study contributes to the manufacturing and technology management research by exploring the impact of supplier centrality on innovation value. The results of this study shed light on the importance of a firm's central network position in enhancing the impact and quality of innovation. This study uncovers contingencies that help realize the potential benefits of holding a central network position.

This study aims to examine the trend of industrial competition between the US and China, which is the most crucial determinant in the future development of the global economy. For decades, the global economy has strengthened the global production network based on the division of labor between countries. Thus, the ripple effect of competition between the two countries should be analyzed in terms of the global production network. Therefore, this study uses the product space model, which explains the development process of industries with comparative advantage by country. We constructed the model based on the products of HS 4-digit code for the 2010–2019 period. The analysis results on the trend of the industrial competitiveness of major countries are as follows. First, the current industrial competitiveness of China is concentrated on low-tech industries. In the case of high-tech items, China shows a tendency of lower export sophistication compared to major manufacturing powerhouses such as Germany, the US, Japan, and Korea. Second, with respect to the possibility of a future industrial structure upgrade evaluated by density, the trend of China overtaking other manufacturing powerhouses is observed. As implied by the product space model, the advancement of the industrial structure through active participation in international trade enhances the industrial competitiveness. Therefore, the outcome of US-China industrial competition depends on who ensures more openness and industrial complexity.