Collaborative Innovation Capability Research Articles

How Does Knowledge Management Matter for Supply Chain Resilience?

Disruption events highlight the importance of supply chain resilience (SCR) and leave managers wondering what characteristics can help firms survive and recover. This study employs the knowledge-based theory to investigate factors contributing to SCR. Using data collected from 220 manufacturing firms in China, this study empirically examines the proposed research model. Results indicate KM processes (i.e., creation, sharing, utilization) significantly influence SCR, with collaborative innovation capability (CIC) mediating the relationship between KM and SCR. Interestingly, social media use positively moderates the relationship between knowledge sharing/utilization and CIC, while this effect is absent for the relationship between knowledge creation and CIC. These findings enrich the existing literature on knowledge management and supply chain management, offering managerial insights for effective knowledge strategies and resilience improvement.

The contribution of digital business strategy in enhancing collaborative innovation capability: The moderating role of organizational culture—A case study of six pharmaceutical companies in Jordan

AbstractWith innovation becoming more collaborative, the influence of digital business strategy (DBS) on interfirm cooperation has grown. This study investigates how DBS can enhance collaboration innovation capabilities across pharmaceutical companies in developing countries. Further, it investigates organizational culture as a moderating variable in the relationship between DBS and collaborative innovation capability (CIC). A total of 205 questionnaire responses were gathered on six Jordanian pharmaceutical corporations. The findings showed that each DBS element (development, objectives, resources, management capabilities, and digital leadership) positively affected CIC, and that organizational culture positively moderated the relationship between DBS and CIC. These results provide valuable insights for managers seeking to improve collaborative capability by leveraging digital business strategies and organizational culture.

Research on Collaborative Innovation Evaluation of Intelligent Logistics Park

The collaborative innovation capability of intelligent logistics parks plays a crucial role in promoting their development, but still encounters various problems in terms of progress. On the basis of summarizing the evaluation indexes and methods of collaborative innovation capability in logistics systems, this article constructs an evaluation index system from three dimensions of intelligence, collaboration capabilities, and innovation capabilities using the combined principal component analysis and data envelopment analysis (DEA). In this empirical article, 18 intelligent logistics parks in the upper, middle, and lower reaches of the Yangtze River Economic Belt are taken as the research objects to analyze the key factors influencing collaborative innovation of practical intelligent logistics parks. Results show that, on the one hand, the collaborative innovation process of many intelligent logistics parks have redundant inputs and outputs, which leads to failure of realizing DEA effectively; on the other hand, gaps in the collaborative innovation level leads to failure of realizing the overall coordinated development. The level of economic development cannot completely determine the level of collaborative innovation of the intelligent logistics park.

Retracted: Prediction Algorithm of Collaborative Innovation Capability of High-End Equipment Manufacturing Enterprises Based on Random Forest

Retracted: Prediction Algorithm of Collaborative Innovation Capability of High-End Equipment Manufacturing Enterprises Based on Random Forest

Micro-foundations of a Collaborative Sustainability-oriented Innovation Capability

Micro-foundations of a Collaborative Sustainability-oriented Innovation Capability

The mechanism of innovation-driven emerging technology generation based on big data fusion in the perspective of technological self-reliance and self-improvement

Abstract Emerging technologies create opportunities for later adopters to achieve technological and economic leapfrogging and are highly valued by governments and enterprises. In this paper, we first screen the key factors influencing innovation drive through data region feature extraction to achieve a synergistic innovation effect between collaborative innovation and R&D subjects. Secondly, the multidimensional data are fused, and the feature extraction is performed using Transformer’s encoder (Encoder) structure, and the bidirectional coding of the input sequence text is realized using the supporting MLM training method. Finally, by comparing the analysis with other multimodal fusion methods in the constructed real dataset, the high performance of this method on emerging technology innovation-driven problems is demonstrated. The experimental results show that the absolute path coefficient of the innovation environment on collaborative innovation capability is 0.728 and the standardized coefficient is 0.835, which indicates that the innovation environment has a significant positive correlation with the innovation capability of emerging technology R&D subjects. The innovation-driven performance of science and technology emerging technology generation mechanism based on big data fusion technology is improved by 34.2%. The innovation-driving model based on big data fusion technology proposed in this paper plays a positive role in promoting the agglomeration of emerging industries and effectively improves the innovation ability and the conversion rate of R&D results of emerging enterprises, which is of great strategic significance for future economic development.

Research on the Influencing Factors and Transformation Path of Logistics Enterprise Low-Carbon Performance

Purpose - This study expounds that logistics enterprises should make use of an information-sharing mechanism, benefit distribution mechanism, and government guarantee mechanism to optimize and balance resource allocation with cooperative participants.
 Design/Methodology/Approach - This study developed a theoretical research model with interface management analysis, interface resource allocation, and interface management measures as independent variables; an interface connection mechanism and collaborative innovation capability as intermediary variables; and the low-carbon performance of enterprises as a dependent variable based on the structural equation model (SEM) and the empirical test, by selecting a certain number of logistics enterprises nationwide as research objects.
 Findings - This study discloses that elements such as interface management analysis, interface resource allocation, interface management measures, interface connection mechanism, and collaborative innovation capability contribute proportionally to the low-carbon performance of logistics enterprises. Meanwhile, the interface connection mechanism plays an intermediary role in the impact of interface management analysis and interface management measures on the low-carbon performance of enterprises.
 Research Implications - This study proposes that the collaborative innovation capability of enterprises should be improved through various interface management measures, and that R&D and the application of low-carbon technology and equipment must be accelerated, thus promoting the improvement of the low-carbon performance of enterprises, and enabling a low-carbon transformation in logistics enterprises, and even the whole logistics industry, so as to help achieve the carbon peak and move toward carbon neutrality as soon as possible.

Research on digital sharing mechanism of agricultural science and technology resources considering collaborative innovation capability

The digital sharing of agricultural scientific and technological resources is the key to promoting agricultural scientific and technological innovation. Explore the strategic mechanism for the digital sharing of agricultural scientific and technological resources, reveal the law of their behavioral evolution, and provide theoretical guidance for the practice of digital sharing of agricultural science and technology resources. Introducing the perspective theory of perceived utility to replace expected utility, constructing a stochastic evolutionary game model for the sharing parties and demand parties of agricultural science and technology resources, analyzing the dynamic evolution rules of both sides of resource sharing, and analyzing the key factors affecting the stability of agricultural science and technology resource sharing through numerical simulation.

Local University Cultivation Model Research on Specialized Software Engineering Talents Under Integration of Production and Education

In the context of the new era, cultivating high-quality innovative talents and technical skills has become an urgent requirement to promote the development of the software industry. There are some problems in the training of specialized software engineering talents in local universities in China, such as unclear orientation, ineffective practical teaching effect and shortage of professional teachers. Based on the issues mentioned above, it is advisable to establish a clear professional orientation aligned with industry demands and develop a curriculum system and content that are in line with this specialized focus. Establishing a collaborative industry-education-research practical teaching system and deepening the collaborative innovation capability development model between industry, education, and research. By solving the two core problems of 'what kind of professional talents to cultivate ' and 'how to cultivate '. It aims to provide suggestions for the professional cultivation of software engineering talents in local colleges and universities in the era of industry-education fusion.

Investigating the effect of university enterprise collaboration on individual innovation in underdeveloped regions

<abstract> <p>The innovation capability index of underdeveloped regions lags far behind that of the eastern coastal areas. This imbalance in innovation capability poses a critical challenge for underdeveloped regions in implementing its innovation-driven development strategy and economic transformation. Individual collaborative innovation ability is an essential skill that allows individuals to transform knowledge and resources into economic value. Presently, research on individual collaborative innovation capability focuses only on the external environment, cooperation mode and benefit allocation. This approach fails to reveal how organizational factors affect individual collaborative innovation capability, and there is a lack of research on underdeveloped regions. Collaborative innovation theory proposes that deep cooperation between industries or institutions through acquiring resources and knowledge can have a positive impact on other environments. Improving individual collaborative innovation capabilities must be achieved through the integration of heterogeneous innovation resources owned by the two core innovation entities, to achieve full integration of innovation elements. Therefore, collaborative innovation theory can effectively address this problem. This article adopts a quantitative research method. A sample of 911 teachers was selected from thirty vocational colleges in Inner Mongolia. The data were analyzed using the Hierarchical Linear Modeling (HLM) model and the proposed relationship was validated. The research findings indicate that cognitive, social and geographical proximity have significant positive effects on collaborative behavior. Collaborative behavior has a significant positive impact on individual collaborative innovation ability. Collaborative behavior plays a mediating role between multidimensional proximity and individual collaborative innovation ability. This study will add information on the collaborative innovation theory, help to understand the formation and impact mechanism of cooperative relationships in school-enterprise cooperation in underdeveloped regions, and thus promote the development of STEM education in underdeveloped areas.</p> </abstract>

Business Analytics and Collaborative Innovation Performance in the ICT Sector

This study aims to investigate the impact of business analytics (BA) capabilities on collaborative innovation, which involves the exchange of ideas and knowledge with external sources on digital innovation platforms. Based on the resource-based view (RBV), BA capabilities were divided into three dimensions: tangible, personal, and intangible. A research model is then developed to describe the relationships among BA capabilities, collaborative innovation capabilities, and collaborative innovation performance. To test the model, data were collected through a questionnaire survey from 167 companies and analyzed using structural equation modeling (PLS-SEM). The results show that BA tangible capabilities have a positive impact on BA personal and intangible capabilities. Both BA personal and intangible capabilities are positively associated with collaborative innovation capability, which in turn was found to be a strong predictor of collaborative innovation performance. These results demonstrate the positive influence of BA in driving collaborative innovation performance.

Sustainable collaborative innovation capability enhancement paths of marine ranching: Supernetwork analysis perspective

In order to solve the problem of weak innovation ability of marine ranching enterprises, it is necessary to establish a collaborative innovation system involving multiple subjects to break the innovation boundary of enterprises. At the same time, because the collaborative innovation system of marine ranching is a complex network system, this paper designs the supernetwork model of collaborative innovation in marine ranching based on supernetwork theory, by analyzing the operation mechanism of relationship coordination network, resource sharing network and cooperative innovation network in supernetwork, solving the network equilibrium conditions and the path to realize supernetwork equilibrium based on variational inequality. Through numerical examples, this paper draws the following conclusions: (a) When the relationship coordination network, resource sharing network and cooperative innovation network all reach equilibrium, the marginal total cost of the three networks is equal to the marginal total value, the cooperative innovation super network of marine ranching reaches equilibrium state; (b) the supernetwork model of collaborative innovation in marine ranching needs to go through two states: “initial-intermediate” and “intermediate-equilibrium” to achieve equilibrium. Finally, this paper puts forward suggestions on the behavior of the participants to ensure the stable operation of the marine ranching collaborative innovation system.

High-Performance Level and Innovation Capabilities in the Aerospace Industry of Mexico: A Qualitative Comparative Analysis

This paper analyzes the necessary and sufficient conditions for successful innovation in design and engineering companies (DECs) of the aerospace industry in Mexico. It is argued that successful innovation activity is a condition for achieving a high-performance level (HPL) among DECs. Seven innovation capabilities are analyzed to determine whether an HPL exists. Based on the dynamic capabilities approach, this research suggests that learning capability (LRC), research and development capability (RDC), creative capability (CRC), collaborative innovation capability (CIC), knowledge sharing capability (KSC), and exploitation capability (EXTC) are necessary conditions to achieve an HPL in DECs of the aerospace industry in Mexico. The fuzzy-set qualitative comparative analysis (fsQCA) methods are applied in this research to get insight into the configuration complexity that determines configurational causal relationships between HPL and innovation capabilities among firms of this industry in Mexico.

Research on the influence of talent ecosystem on firm innovation performance: Based on the mediating role of collaborative innovation

This paper extends previous studies on the organizational innovation by analyzing the impact of talent ecosystem on firm innovation performance in innovative enterprises. In addition, the mediating effect of collaborative innovation on the relationship between talent ecosystem and firm innovation performance is analyzed. Grounded in the Resource -Based View (RBV) theory, this paper develops an integrative research model which analyzes those relations using structural equation modeling on a dataset of 176 innovative enterprises. Results suggest that talent competence, organizational environment and regional environment of talent ecosystem have a significant positive impact on collaborative innovation, and organizational environment has a stronger effect on collaborative innovation; talent ecosystem can influence innovation performance to different degrees through the mediating role of collaborative innovation (technology synergy and capability synergy); technology synergy in collaborative innovation positively affects innovation performance, while Technology synergy in collaborative innovation positively affects innovation performance, while capability synergy has no significant effect on innovation performance. The findings of the study provide new ideas for enterprises to improve talent ecosystem and enhance innovation performance.

EXAMINING THE INFLUENCE OF ENVIRONMENTAL TURBULENCE ON FIRM INNOVATION PERFORMANCE IN EMERGING MARKETS: USING AN ENVIRONMENT-STRATEGY-PERFORMANCE FRAMEWORK

Evidence suggests that turbulent environment exposure is a significant driving force for business innovation. The automotive industry is strongly influenced by environmental dynamics due to continuous technological changes. Car OEMs require an accurate landscape of industrial uncertainties. The purpose of this study is to investigate the role of business environmental turbulence (BET) in innovation performance. Applied to the environment-strategy-performance framework and underpinned by the dynamic capability view (DCV) and contingency theory, our research model concerns both the antecedent and moderation roles of BET in innovation performance. A sample of 306 questionnaire data is collected from the management of Iranian automotive firms, and PLS-SEM is used for the analysis. The results suggest that BET improves innovation performance through enhancing networking capability (NC) and collaborative innovation capability (CIC). Besides, BET positively moderates the relationship between NC and innovation performance. This study contributes to understanding business innovation in a turbulent environment setting. Our findings offer important implications for managers to set strategies, particularly in a dynamic environment.

Path optimization of open collaborative innovation of energy industry in urban agglomeration based on particle swarm optimization algorithm

To study the open collaborative innovation path optimization of urban agglomeration energy industry based on particle swarm optimization algorithm. Firstly, this paper brings industrial agglomeration and urban agglomeration into a unified analytical framework, uses location entropy and spatial Gini coefficient to measure the degree of industrial agglomeration, and evaluates the degree of regional industrial agglomeration competitiveness by constructing an evaluation index system of industrial agglomeration competitiveness. Then, the agglomeration index system was established, the development degree analysis method and Carlino model were used to analyze the development degree and agglomeration degree of eco-economic zones, and the agglomeration effect was analyzed by dynamic econometric method and spatial autocorrelation statistical method. Finally, a regional collaborative innovation capability evaluation model based on particle swarm optimization algorithm is constructed. Based on the index system and evaluation model, this paper evaluates and analyzes the collaborative innovation capability, and puts forward countermeasures and suggestions for future collaborative development.

Research on the Influence of Collaborative Innovation Network Structure and Innovation Capability in the Yangtze River Economic Belt

This paper uses the modified gravity model to establish the collaborative innovation network among 110 cities in the Yangtze River Economic Belt from 2009 to 2018, and uses social network analysis and dynamic panel model to study the impact of innovation network structure on the level of collaborative innovation. The results show that: (1) The collaborative innovation network connection level of the Yangtze River Economic Belt is relatively low, showing a spatial distribution pattern of “high in the east and low in the west”, and the degree of network connection is not high, and the network structure is relatively loose. (2) The power of network structure significantly promotes the improvement of the level of collaborative innovation, but the improvement effect has certain differences, which is embodied in the promotion effect of proximity centrality is greater than that of degree centrality is greater than that of intermediate centrality. The degree of influence of network structure power varies.

Improved Intuitionistic Fuzzy Entropy and Its Application in the Evaluation of Regional Collaborative Innovation Capability

Intuitionistic fuzzy entropy is an important concept to describe the uncertainty of intuitionistic fuzzy sets (IFSs). To fully measure the fuzziness of IFSs, this paper comprehensively considers the deviation between membership and non-membership and the influence of hesitation, constructs the general expression of intuitionistic fuzzy entropy based on special functions, and proves some of its major properties. Then, it is verified that some existing intuitionistic fuzzy entropies can be constructed by specific functions. Finally, based on a specific parametric intuitionistic fuzzy entropy, this paper applies it to evaluate the regional collaborative innovation capability, to verify the feasibility and practicability of the entropy. In addition, the effectiveness and practicability of this entropy in decision making are further illustrated by comparing it with other entropy measures.

How do Chinese SMEs enhance technological innovation capability? From the perspective of innovation ecosystem

PurposeThe purpose of this study is to investigate the influence mechanisms of multi-level ecological participants on technological innovation capabilities within the focal small and mid-size enterprises' (SME) innovation ecosystem. The author examines the moderating role of the innovation ecological environment.Design/methodology/approachWith the lenses of innovation ecosystem theory, technological innovation theory and ecological theory, the author constructs and empirically tests a conceptual framework for exploring the effects of the focal SME's connections with universities and research institutions, and the industrial chain and ecosphere on their independent and collaborative innovation capabilities. The innovation ecological environment is employed as a moderating variable in the proposed model. The author issued email questionnaires to managers at innovative SMEs in Shenzhen, Shanghai and Jiangsu provinces. The data were used for multiple regression analyses to test the hypotheses.FindingsAs predicted, the author found that SMEs’ cooperation with universities and research institutions positively affects independent and collaborative innovation capability. The relationships between the industrial chain, the ecosphere and independent and collaborative innovation capabilities are all inverted U-shaped. Additionally, the author demonstrates that the innovation ecological environment positively moderates relationships between the focal SME's ecological participants and these two types of technological innovation capabilities.Originality/valueThe results enrich research on innovation ecosystems and technological innovation capability and provide important managerial implications for Chinese SMEs to enhance their technological innovation capability by constructing and coordinating innovation ecosystems. It also allows China, as well as other developing countries, to cultivate world-class enterprises as an innovative nation.

Prediction Algorithm of Collaborative Innovation Capability of High-End Equipment Manufacturing Enterprises Based on Random Forest

This paper studies the competitiveness of listed companies in high-end equipment manufacturing industry by using random forest. Random forest is a supervised machine learning algorithm that is actually based on the regression and classification. It takes some important decisions that are always based upon the set of samples. It counts majority for the classification purposes while it takes an average for the regression. For empirical analysis, 88 listed companies are selected. It is found that there are great differences in comprehensive competitiveness among industries. Enterprise scale accounts for a high proportion in the comprehensive competitiveness, and its score often affects the comprehensive strength; and the gap between companies in the same industry is also obvious. The empirical evaluation results of this paper provide three enlightenments for enterprises to improve their comprehensive competitiveness, such as seizing the strategic opportunity to expand the market, expand the scale of enterprises, improve asset management, and narrow the industry gap.