Search results

The purpose of this study is to identify the factors determining collaborative innovation effect of manufacturing firms in emerging economies.

Based on a survey of 1,206 Chinese manufacturing firms and using structural equation modelling, this study explores the factors determining the effect of collaborative innovation among manufacturing firms (namely, internal capabilities, government policies, collaboration mechanisms and social networks) and examines the relationship between collaborative innovation effect and innovation performance.

The study finds that there are significantly positive relationships between firms’ internal capabilities, government policies, collaboration mechanisms and social networks and collaborative innovation effect among firms.

These findings reveal that policymakers should create an effective institutional culture and market environment to facilitate firms’ collaborative innovation.

This paper draws on the resource-based view of firms and contributes to understanding of how the development of factors determining firms’ collaborative innovation effect can improve innovation performance. This study extends established frameworks on collaborative innovation in relation to four dimensions, namely, firms’ internal capabilities, government policies, collaboration mechanisms and social networks, uniquely identifying the limits of specific dimensions. Moreover, this study addresses government policies and “Guanxi culture” specific to China that provide new insights into how firms’ collaborative innovation is improved from the perspectives of business–governmental relations and social networks.

Given that women around the world face more exclusion in terms of limited access to economic and innovation activities than men do, it is understandable that some female-led start-ups in weak institutional environments engage in bribery to help reduce the difficulties they encounter in the face of intense business competition. However, the link between bribery and product innovation performance is unclear. The purpose of this study is to investigate the relationship between bribery and product innovation performance for female-led start-ups, as well as the roles of institutional support and self-control in this link.

This empirical study evaluates survey data from female-led manufacturing start-ups in China's Yangtze River Delta region to investigate the relationship between bribery and product innovation performance.

This research shows that bribery has an inverted U-shaped impact on product innovation performance in female-led manufacturing start-ups, meaning that the product innovation performance of these firms initially increases but then decreases as the bribery intensity (i.e. the frequency and amount of bribes) increases. The authors also focus on the roles of institutional support and self-control in this link, where the authors find that this relationship is steeper for firms with strong institutional support, as well as for individual female entrepreneurs who have high levels of self-control.

The findings of this study indicate that policymakers should undertake efforts to improve institutional quality (e.g. increasing clarity around decisions, providing more institutional support, etc.) and to guide female entrepreneurs to cultivate higher levels of self-control, as such efforts would reduce the appeal of, and the opportunity for, bribery.

To date, very few studies focus specifically on female-led enterprises in the field of bribery research. The research findings presented here on the effect of bribery in female-led start-ups on firm product innovation performance are useful to researchers, policymakers and businesspeople, as they provide a better understanding of bribery in female-led start-ups in China, which can also be extrapolated to encompass other transition economy contexts.

This study aims to construct a theory of multi-dimensional organizational innovation cultures and innovation performance in transitional economies and explore the moderating effect of team cohesion on this theoretical relationship.

Using data collected from 175 manufacturing firms in transitional economies, this study constructs a new theory framework of multi-dimensional organizational innovation cultures (knowledge sharing, organizational innovation atmosphere, team decision-making and organizational change) and firms’ innovation performance and also explores the moderating effect of team cohesion on this theoretical relationship.

The findings show that there are positive relationships between knowledge sharing, organizational innovation atmosphere, team decision-making, organizational change and innovation performance of firms. Furthermore, team cohesion plays a positive moderating role in this relationship.

It extends the general understanding of multi-dimensional organizational cultures management in the context of transition economies by exploring the differences between the Chinese and Vietnamese firms in terms of the impact of organizational innovation culture on innovation performance.

This study constructs a new theory framework of multi-dimensional organizational innovation cultures along the four dimensions of knowledge sharing, organizational innovation atmosphere, team decision-making and organizational change. These factors together have rarely been examined before. Hence, the findings extend existing research on organizational cultures management. Moreover, a new idea for this study is that the authors consider team cohesion as a moderating variable between organizational innovation culture and innovation performance of firms, hence providing both theoretical discussion and empirical validation of the impact of team cohesion on this relationship. It thus extends existing research on the team theory.

Open innovation enables firms to incorporate external expertise and resources into their innovations. However, it is far from easy to obtain sufficient support from external contributors due to potential concerns about the risks of opportunism and appropriation. This paper aims to investigate whether firms’ engagement in corporate social responsibility (CSR) contributes to their open innovation, considering the contingency factors of technological capability, environmental dynamism and state ownership based on capability and motivation perspectives.

Using a sample of Chinese listed firms covering the period from 2009 to 2018, instrumental variable and propensity score matching approaches were used to address the endogenous problems.

This paper obtains empirical results showing that firms engaged in higher levels of CSR produce more joint outputs (co-owned patents) and that this effect is strengthened by technological capability and environmental dynamism. Among state-owned enterprises, CSR engagement is less impactful with regard to open innovation. It is further shown that open innovation is a primary channel through which CSR engagement enhances innovative efficiency.

This study enriches the knowledge of the antecedents of open innovation and contributes to the debate regarding the relationship between CSR and innovation by establishing a relationship between CSR and open innovation, whereas most prior studies focus on how the input and output of innovation are affected by CSR initiatives.

Family businesses often lack sufficient knowledge about digital business model innovation digital business model innovation (BMI). This study's purpose was to analyze how and when organizational readiness for digital innovation exerts a positive impact on family businesses' digital BMI. To do so, the authors examined the mediating effect of the familiness learning mechanism and the moderating effect of family involvement on this relationship.

A quantitative survey method was used to collect the data for this study. Using a sample of 282 family businesses involved in manufacturing in China, the authors conducted hierarchical regression analyses to evaluate the authors' theoretical model.

The results of this work demonstrate a positive relationship between organizational readiness for digital innovation and family businesses' digital BMI, and the find that the familiness learning mechanism mediates this relationship. The findings also show that second-generation family involvement in management moderates the direct effect of organizational readiness for digital innovation on the familiness learning mechanism, as well as the indirect effect of organizational readiness for digital innovation on digital BMI via the familiness learning mechanism. Moreover, the results establish that family involvement in ownership moderates the direct effect of the familiness learning mechanism on digital BMI, as well as the indirect effect of organizational readiness for digital innovation on digital BMI via the familiness learning mechanism.

This study provides practical contributions to the literature on family businesses and to public policy, providing concrete suggestions for fostering digital innovation in family enterprises. This study also enriches our understanding of the unique conditions by which family businesses can successfully implement digital BMI.

This research confirms that organizational readiness for digital innovation is an antecedent of digital BMI. This finding offers a new perspective that helps explain what might lead family businesses to engage in digital BMI. This study also places the familiness learning mechanism into a theoretical framework, which expands the current understanding of how organizational readiness for digital innovation facilitates digital BMI. Moreover, this work provides new insights into the boundary conditions by which organizational readiness for digital innovation affects the digital BMI of family businesses in terms of second-generation family involvement in management and family involvement in ownership.

This paper aims to systematically examine the key notion of integration of non-market and market strategies in the increasingly popular study of corporate non-market strategies.

This paper is based on a brief literature review of the non-market strategy (NMS) research that shows the existing literature does not offer a clear and systematic account of the key notion of integration. It suggests any systematic account of integration should address at least three interrelated questions, i.e. why, what and how to integrate non-market and market strategies?

For the why question, the authors use a formal model to demonstrate that the essence of the most important type of integration synergy lies in the positive spillover or externality from non-market to market strategies. For the what question, the authors identify the contents of integration at three levels, i.e. the level of non-market environment analysis, the level of NMS choice, and the level of non-market dynamic interactions. For the how question, the authors argue that the combination of non-market and market strategies should be seamless in terms of horizontal, vertical and intentional coordination. Overall, the authors argue, only when the right contents are combined and seamlessly coordinated will there be high synergies from integration of non-market and market strategies.

Managers are advised to give non-market strategies full attention. Managers charged with non-market tasks should explore how to seamlessly coordinate non-market and market strategies in order to gain maximal synergies.

This paper is the first to examine the key notion of integration in a systematic manner. It is the first to propose a three-question solution to systematic understanding of the notion and the first to propose the seamless coordination concept and its associated three aspects of seamless coordination.

The purpose of this study is to calculate the frequency electric field in substation.

The paper proposes a novel fast multipole method (FMM) called Super-FMM to solve the PFEF problems in substations. The paper substitutes the original approaches for analytic expansions and translations through equivalent density representations.

The paper shows that the Super-FMM is more efficient in terms of the complexity of its storage spaces and computational costs compared with the best-known FMM when placed under scenarios with exactly the same error rates.

Using the fast Fourier transform algorithm can further improve the optimization algorithm and computational efficiency.

A novel FMM called Super-FMM is proposed, which has a structure similar to that of the adaptive FMM algorithm, but the paper substitutes the original approaches for analytic expansions and translations through equivalent density representations.

Taking the lens of a cue diagnosticity framework and affective primacy theory, this study aims to examine the relative effects of cognitive and affective country image on consumer cognitive judgement, affective evaluation and behavioural tendency in one integrated model. It also explores how the direct effects may vary with the intra-valence nature (ambivalent vs. univalent) of cognition-affect.

The proposed research model was tested using data from a large Chinese sample and consumer responses to products from four countries − the USA, Japan, Brazil and India.

The results show that the relative effects of cognitive and affective country image are complex and differ by the intra-valence nature of cognition-affect. On a general level, cognitive and affective country image exert equal influence on affective evaluation and behavioural tendency. In contrast, cognitive country image demonstrates a more prominent effect than affective country image on cognitive judgement. Compared with univalent, ambivalent cognition-affect strengthens the positive impact of affective country image but does not significantly alter the positive impact of cognitive country image on consumer reactions.

This research contributes to the ongoing debate regarding implications of two focal aspects of macro country image by revealing their relative importance in an integrated framework and enriches country-of-origin research through unveiling the uni/ambivalent cognition-affect as a moderator of the relationship between cognitive/affective country image and consumer reactions. The research findings provide implications as to whether and when marketing strategies should focus on leveraging positive (negative) cognitive or affective country image.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.