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This study aims to explore the effect of competitive aggressiveness on firm performance and the moderating effect of firm 2019s ego-network structures in the international coopetition network.

From the perspective of strong cooperation of the global automobile industry in recent years, this study uses the global automobile firms in Factiva database as samples to test hypotheses using the least squares dummy variable (LSDV) model.

This study finds that there is different relationship between the number and variety of competitive actions and firm performance. In addition, ego-network structures have different coefficients for the number and variety of competitive actions.

The conclusions provide theoretical support and policy suggestions for firms to develop effective competitive strategies according to ego-network structures in the international coopetition network.

This paper aims to examine how the firm’s global coopetition network position impacts market share and to explore the multiple moderating effects of trade network strength and structures on the relationship between firm global coopetition network position and market share.

This paper selects global automobile manufacturing firms as samples whose classification is “Automobile” in the Factiva database from 2014 to 2018 and develops the measurement for global coopetition network and trade network by using Ucinet6. Finally, Stata was used for data analysis.

This paper finds that structural holes and centrality are beneficial to improve global market share. And the trade network strength and structures have positive multiple moderating effects on the relationship between the firm global coopetition network position and market share.

This paper explores industrial international competitiveness according to the intricate trade relations among countries and the impact of industrial international competitiveness on the relationship between global coopetition network position of brand firms and market share. The results of this paper expand the current literature on the relationship between characteristics of coopetition network and trade network.

The authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the characteristics of a firm's whole network and ego-network in a transnational coopetition network influence network performance.

The authors analyzed the public news of the sample firms about the coopetition by structural content analysis to build the coopetition networks and access to data on the competitive actions of firms. Then, to measure the variables associated with the coopetition network, such as the structural hole, centrality and ego-network stability, the authors use UCINET 6 that is a widely used piece of software for social network analysis to establishing five undirected binary adjacency matrices.

The authors find that a firm's competitive aggressiveness mediates the relationship between a firm's whole network position and network performance that emphasizes the need for integrating competitive dynamics research and coopetition research and shows how valuable insights can be gained through such integration. And the interaction of structural hole and centrality impacts competitive aggressiveness and network performance, and the interaction is different under high and low ego-network stability. The integration of whole network and ego-network literature studies provides new insights into firm network literature.

In the process of cooperation, firms should consider whether they can occupy the structural hole and center as important indicators for partner selection. Too stable relationship will prevent firms from obtaining new resources. Firms should weigh the period of cooperation according to specific situation.

These results indicate that ego-network stability, as an important complementary characteristic of coopetition network, has a significant synergistic effect with structural holes and centrality on competitive aggressiveness and network performance. And these findings expand the current literature on the relationship between characteristics of network, competitive aggressiveness and network performance.

This study aims at the sudden outbreak of COVID-19, which had an unprecedented negative impact on the Chinese economy, with firms being affected most. Firms differ in terms of their specific internal environment, shaping their ability to respond to the outbreak, so the impact may also vary.

In this paper Chinese listed firms are selected as samples to investigate the mediating effect of prior digital technology on the relationship between R&D (research and development) investment (funds and staff) and firm performance during the epidemic. Firm size and diversification are then introduced as moderating variables to explore the conditional mediating effect of digital technology.

The results indicate that the higher the firm's prior R&D investment, the higher its digital technology level, and thus the stronger its resistance to the epidemic. Moreover, compared with large-scale firms, small-scale firms have the advantage of strategic flexibility to technological changes, which can help them accumulate experience from R&D activities for digital transformation, thus attenuating the negative impact of the COVID-19 on firm performance. Finally, the results also show that digital technology mediates more strongly between R&D investment and firm performance in diversified firms than in centralized firms.

The study builds a mediation model to reveal the process mechanism through which R&D investment affects firm performance via digital technology. Firm size and diversification are then innovatively introduced as situational factors to build the moderated mediation model, which opens up a new perspective for understanding the effect of firm internal factors on the relationship between R&D investment, digital transformation and firm performance.

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters conveniently and achieve high measurement accuracy.

A stiffness and kinematic measurement principle of the integrated system is proposed, which considers the influence of robot weight and load weight on measurement accuracy. Then an error model is derived based on the principle that the coordinate of sphere center is invariant, which can simultaneously identify the parameters of joint stiffness, kinematic and hand-eye relationship. Further, considering the errors of the parameters to be calibrated and the measurement error of 3D camera, a method to generate calibration observation data is proposed to validate both calibration accuracy and parameter identification accuracy of calibration method.

Comparative simulations and experiments of conventional kinematic calibration method and the stiffness and kinematic calibration method proposed in this paper are conducted. The results of the simulations show that the proposed method is more accurate, and the identified values of angle parameters in modified Denavit and Hartenberg model are closer to their real values. Compared with the conventional calibration method in experiments, the proposed method decreases the maximum and mean errors by 19.9% and 13.4%, respectively.

A new measurement principle and a novel calibration method are proposed. The proposed method can simultaneously identify joint stiffness, kinematic and hand-eye parameters and obtain not only higher measurement accuracy but also higher parameter identification accuracy, which is suitable for on-site calibration.