scholarly journals Innovation Model of China's High-End Equipment Industry: Do Social Capital and Dynamic Capabilities Matter for the COVID-19 Crisis?

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuhong Ai ◽  
Diyun Peng

This paper explores the different model combinations of enterprise innovation in China based on the roles of social capital and dynamic capabilities. We implement Qualitative Comparative Analysis to understand the non-linear asymmetric relationships better. We use the data of 44 Listed Companies in China's high-end equipment manufacturing industry and find that three innovation models (the market-oriented independent innovation, government-supported technological innovation and industry-supported learning innovation models) are valid. Social capital, dynamic capabilities, and intra-industry networks are the main determinants of these innovation models. We also discuss the implications of these innovation dynamics on Chinese enterprises as a way to sustain the economy's high-quality development, including during the era of the COVID-19 pandemic crisis.

2021 ◽  
Vol 13 (17) ◽  
pp. 9878
Author(s):  
Lei Shen ◽  
Cong Sun ◽  
Muhammad Ali

The structure of the manufacturing industry has forced manufacturing companies to understand the importance of digitalization and servitization transformation, in terms of production and R&D. In this study, we examine the relationship between servitization, digitization, and enterprise innovation performance through the lens of dynamic capabilities within enterprises. We also discuss the impact of the transformation servitization strategy on business innovation, and the mechanisms by which it impacts business innovation performance. The study’s findings indicate that servitization significantly contributes to innovation performance, and digitalization acts as a mediating mechanism between the proposed relationships. Thus, this article argues for the integration and growth of servitization and digitization.


Author(s):  
Cuilan Wang ◽  
Deji Wang ◽  
Yu Wang ◽  
Fangyuan Jiao

In order to study the development trend of the Internet’s role in supporting enterprise innovation, a new method based on deep learning algorithm and knowledge graph technology is proposed. Experiments show that the accuracy, F1 value, recall rate and precision of the algorithm are distinctly improved compared with the existing algorithms. A new algorithm is applied to analyze the innovation evolution of Chinese enterprises, using papers, patents and other documents between 1905 and 2020 as data sources. Based on the experimental results, the development stages can be divided into five stages. The research focus is on product R&D innovation, manufacturing innovation, marketing innovation, resource allocation innovation and organizational innovation. It can be seen that the development process of the Internet supporting enterprise innovation system is an evolutionary development process from point to line, to surface, to the body, and to the ecosystem.


2016 ◽  
Vol 9 (8) ◽  
pp. 1 ◽  
Author(s):  
Yu-Li Lin ◽  
Hsiu-Wen Liu ◽  
Fengzeng Xu ◽  
Hao Wang

<p>This study addresses the important question of causal complexity as it relates to the influence of social capital, entrepreneurial alertness and the entrepreneurship environment on business performance. Using a relatively new methodological approach, namely fuzzy-set qualitative comparative analysis (fsQCA), this paper aims to investigate alternative complex antecedent conditions (or causal recipes) that lead to high performance. Based on a survey of 194 entrepreneurs in China, this paper shows that business performance is likely to be the result of a combination of causal factors. This study finds that: (1) four different configurations of social capital, entrepreneurial alertness and entrepreneurship environment were “equifinal” causes of high performance, and (2) market openness should fit other environmental conditions to achieve high performance. This study contributes to research on entrepreneurship by applying the ideas of “equifinality” and “fit” to entrepreneurial characteristics and environment theory.</p>


2018 ◽  
Vol 56 (6) ◽  
pp. 1217-1231 ◽  
Author(s):  
Marta Peris-Ortiz ◽  
Carlos Alberto Devece-Carañana ◽  
Antonio Navarro-Garcia

PurposeThe purpose of this paper is to investigate the relationship between open innovation (OI) and radical and incremental innovation success in knowledge-based companies. The company’s human resources and organizational learning capability are considered as the fundamental nexus of this relationship.Design/methodology/approachAt the conceptual level, the paper analyzes the relationships between dynamic capabilities and OI and between OI and innovation success. Fuzzy-set qualitative comparative analysis (fsQCA) was used to study how innovation is implemented in 29 companies.FindingsFsQCA identifies combinations of factors that facilitate incremental innovations. These combinations reveal the path to implementing company policies that enable incremental innovation and foster radical innovation.Research limitations/implicationsThe nature of the study sample means that the findings should be generalized with precaution. The most valuable implication is the identification of combinations of factors that help companies manage innovation.Originality/valueScarce literature links organizational learning factors and OI to different types of innovation. The use of fsQCA to analyze the cases also marks a breakthrough in the innovation literature.


2019 ◽  
Vol 32 (2) ◽  
pp. 154-173 ◽  
Author(s):  
Vasiliki Kosmidou ◽  
Manju K. Ahuja

This article develops an integrated framework for the examination of innovation drivers in small and privately owned family firms. Drawing from the family-driven innovation model, we study how factors at the family, the firm, and the environment level combine into distinct configurations that spur innovation. Analyzing 277 family firms using fuzzy-set qualitative comparative analysis, we find six configurations leading to high innovation and show that none of the antecedents is necessary for it. Building inductively on our configurations, we also derive propositions about the combinations of factors leading to high innovation. Implications for research and practice are discussed.


2018 ◽  
Vol 36 (2) ◽  
pp. 195-209 ◽  
Author(s):  
Job Rodrigo-Alarcón ◽  
Pedro M. García-Villaverde ◽  
María J. Ruiz-Ortega ◽  
Gloria Parra-Requena

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