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The authors attempt to answer the basic questions: How is imitation tied to innovation? This question is addressed in the context of China's innovation system in the 2000s where Chinese industrial firms simultaneously implement innovation and imitation strategies in their new product developments.

The authors first build on lattice theory and supermodularity theory to provide a rigorous and careful mathematical proof. The authors further conduct the empirical analyses using an original data on Chinese manufacturing firms' innovation and imitation strategies in the development of new products in 2002.

This article reveals the complementarity relation between imitation and innovation strategies and identifies external knowledge search as the boundary condition that influences the extent to which two strategies reinforce each other.

The findings of the imitation-innovation complementarity suggest that imitation is not only an indispensable strategy independent of innovation, but also is vital to the effectiveness of innovation itself.

The imitation-innovation complementarity finding provides some evidence for the contention that Chinese latecomers exploit the synergies of imitation and innovation, transforming themselves from imitators to innovators and vibrant competitors in the global market (Wu et al., 2016) and, as a result, national innovation system has evolved from a state-sponsored imitation program to the imitation-innovation mixture.

In contrast to earlier innovation studies in which innovation and imitation are unrelated, this study reveals that imitation complements innovation, and the extent of Chinese firms' external knowledge search affects the complementary relationship between imitation and innovation. These findings add important insights to the innovation management literature and contribute empirical evidence to the interplay of innovation and imitation enhancing national innovation system.

The purpose of this paper is to present a coordinated control strategy for stable walking of biped robot with heterogeneous legs (BRHL), which consists of artificial leg (AL) and intelligent bionic leg (IBL).

The original concentrated control in common biped robot system is replaced by a master‐slave dual‐leg coordinated control. P‐type open/closed‐loop iterative learning control is used to realize the time‐varying gait tracking for IBL to AL.

The new control architecture can simplify gait planning scheme of BRHL system with complicated closed‐chain mechanism and mixed driving mode.

Designing and constructing a suitable magneto‐rheological damper can greatly improve the control performance of IBL.

Master‐slave coordination strategy is suitable for BRHL stable walking control.

The concepts and methods of dual‐leg coordination have not been explicitly proposed in single biped robot control research before. Master‐slave coordinated control strategy is suitable for complicated BRHL.

The purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey target decision-making evaluation model to measure the comprehensive effect, so as to select the leading industries of Kashgar urban agglomeration.

First, 18 industries in Kashgar urban agglomerations are taken as objectives, and four indexes, namely, demand income elasticity index, growth rate index, labor productivity growth rate index and contribution rate of output value, are selected to construct an evaluation system for leading industry selection in Kashgar urban agglomerations. Then, grey incidence degree method is used to determine the decision-making power of each decision-making objective. Finally, multi-attribute weighted intelligent grey target decision-making evaluation model is used to measure the comprehensive effect of the objective system of leading industries in Kashgar urban agglomerations.

It can be seen that the multi-attribute weighted intelligent grey target decision-making evaluation model is more convenient to be used in selecting regional leading industries, and the results are accurate and feasible. Based on the calculation results and the actual economic development requirements of Kashgar urban agglomeration, the leading industries of Kashgar urban agglomeration can be determined as: wood processing, furniture, paper making and printing; wholesale and retail; construction; equipment manufacturing; transportation, storage and postal services.

First, it is a new method in selecting regional leading industry by using the multi-attribute weighted intelligent grey target decision-making evaluation model. Second, since there is relatively little research on Kashgar urban agglomeration, especially on leading industries in Kashgar urban agglomeration. The research in this paper can not only enrich the research on selecting leading industries in urban agglomeration but also provide scientific reference for relevant government agencies to formulate economic development plans.