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Purpose The purpose of this paper is to investigate how Chinese firms’ innovation is related to their perceived incentives and pressures from the transitioning institutional environment. Design/methodology/approach A sample of 166 manufacturing firms located in Guangdong Province (China) is analyzed using binomial and moderated multiple regression models. Findings The results show that institutional incentives are more effective in promoting incremental innovations than radical ones, whereas institutional pressures are more pronounced in facilitating radical innovations than incremental ones. In addition, the interaction between the two divergent institutional forces is negatively related to innovation performance. Practical implications The findings inform managers and policy makers in institutional transition environments to consider and balance the effects of institutional forces. Firms should match the institutional incentives and pressures with their own innovation objectives in terms of incremental or radical goals, and take caution to deal with the divergent institutional directions, so as to avoid the negative interaction effects. Policy makers should take a systems approach when considering the incentive-based and/or command-and-control designs of innovation policies and regulations. Originality/value The study contributes to existing literature on institutions and innovation by disentangling incentive and pressure effects of institutions, regulation and innovation policies, as well as the combined and interaction effects intrinsic within institutional mixes.

This article explores the moderating effects of in-house formal R&D and industrial environment turbulence on the relationship between institutional drivers, in terms of incentives and pressures, and firm innovation. Hypotheses were tested on a sample of manufacturing firms in Guangdong Province of China, where institutional changes and governmental policies play prominent roles in shaping innovation. Results show a positive main effect of institutional incentives, but an insignificant main effect of institutional pressures. In-house formal R&D and industrial turbulence negatively moderate the institutional incentives–innovations relationship, yet positively moderate the institutional pressures–innovations relationship. This study links the innovation systems literature with the institution-based view and deepens the understanding of the joint forces of institutional transitions, industrial changes, and resource heterogeneity in shaping innovation. The findings also inform managers and policymakers in institutional transition environments to better manage institutional drivers of innovation by considering firm- and industry-specific characteristics.

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To provide rational, intelligent and real time decision supports to credit risk management for commercial banks, an ANN-based credit risk identification and control method was proposed. A credit risk measurement indicator system was established incorporating both internal and external related factors of debtor firms. And credit risk was identified based on the online learning of an ANN model. To meet the online learning requirement, an improved BP training algorithm with adaptive learning rate and momentum was proposed for speed enhancement. The ANN-based model proposed is suitable for Chinese commercial banks, which only have limited and incomplete historical data due to lagged credit risk management. The model can represent the experience, knowledge and intuitiveness of the experts. And with data accumulation over time, the identification results can be improved through online learning of the ANN model, ensuring objectiveness, rationality and timeliness. An example is given to illustrate the method.