ISSN 0253-2778

CN 34-1054/N

2021 Vol. 51, No. 3

Research Reviews
A literature review of corporate green innovation behavior from the perspective of peer effect and prospect: An integrated theoretical framework
Wan Liang, Zheng Qiaoqiao, Fang Wenpei, Wang Chengyuan, Wang Shanyong
2021, 51(3): 173-184. doi: 10.52396/JUST-2021-0048
How to promote the change of the development mode through corporate green innovations, to realize the balance between economic and social development and environmental quality is an urgent and important research topic.In this sense, the empirical test of the corporate green innovation behaviors is not only among the key interests of academics, but also has strong policy implications. Different from the previous research on it, this paper attempts to start from the new research perspective of peer effects, uses the research history of corporate green innovation behaviors as an entry point, systematically sorts out and analyzes the influencing factors, the mechanism and peer evolution that affect the corporate green innovation behavior.On the basis of this, an integrated theoretical framework is established, and some certain reference for the development of relevant research on corporate green innovation behaviors has been provided.This paper aims to broaden the research perspective of corporate green innovation behaviors, enrich and improve corporate green innovation theories and methods. The research results will help reveal the “black box” of green innovation activities, and provide government guidance for the diffusion of green innovations.
Research Articles:Physics
An ultra-fast C-NOT gate based on electric dipole coupling between nitrogen-vacancy color centers
Shi Shunyang, Ji Wentao, Wang Ya, Du Jiangfeng
2021, 51(3): 185-192. doi: 10.52396/JUST-2020-0039
Our research proposes a new scheme to build a controlled-NOT(C-NOT) gate between two adjacent nitrogen-vacancy (NV) color centers in diamond, using electric dipole coupling between adjacent NVs and selective resonant laser excitation.The electric dipole coupling between two NVs causes the state dependent energy shift.This allows to apply resonant laser excitation to realize the C-phase gate.Combined with a single qubit operation, C-NOT gate can be implemented quickly.Between two adjacent 10 nm NVs, the C-NOT gate can operate up to 120 ns faster than the traditional magnetic dipole coupling method by 2 magnitudes.In order to reduce the effect of a spontaneous emission,we propose to use a non-resonant cavity to suppress the spontaneous emission.The simulation results show that the C-phase gate fidelity can reach 98.88%.Finally, the scheme is extended to a one-dimensional NV spin chain.
Research Articles:Mathematics
Hyperplane arrangement complement with top degree Betti number being small
Li Fenglin
2021, 51(3): 193-195. doi: 10.52396/JUST-2020-1119
The deletion-restriction method was used to classify hyperplane arrangements with the top degree Betti number of its complements being small.
Riemann-Hilbert approach for a mixed coupled nonlinear Schrödinger equations and its soliton solutions
Hu Beibei, Zhang Ling, Fang Fang, Zhang Ning
2021, 51(3): 196-201. doi: 10.52396/JUST-2021-0059
The integrable mixed coupled nonlinear Schrödinger (MCNLS) equations is studied, which describes the propagation of an optical pulse in a birefringent optical fiber. By the Riemann-Hilbert (RH) approach, the N-soliton solutions of the MCNLS equations can be expressed explicitly when the jump matrix of a constructed RH problem is a 3×3 unit matrix. As a special example, the expression of one soliton and two solitons are displayed explicitly. More generally, as a promotion, an integrable generalized multi-component NLS system with its linear spectral problem is discussed.
A hybrid HWENO-based method of lines transpose approach for Vlasov simulations
Wang Kaipeng, Jiang Yan, Zhang Mengping
2021, 51(3): 202-215. doi: 10.52396/JUST-2021-0007
A new type hybrid Hermite weighted essentially non-oscillatory (HWENO) schemes in the implicit method of lines transpose (MOLT) framework is designed for solving one-dimensional linear transport equations and further applied to the Vlasov-Poisson (VP) simulations via dimensional splitting. Compared with the WENO-based MOLT method given in J. Comput. Phys. [2016, 327: 337-367], the new proposed hybrid HWENO-based MOLT scheme has two advantages. The first is the HWENO schemes using the stencils narrower than those of the WENO schemes with the same order of accuracy. The second is that the schemes can adapt between the linear scheme and the HWENO scheme automatically. In summary, the hybrid HWENO scheme keeps the simplicity and robustness of the simple WENO scheme, while it has higher efficiency with less numerical errors in smooth regions and less computational costs as well. Benchmark examples are given to demonstrate the robustness and good performance of the proposed scheme.
Subgroup analysis for multi-response regression
Wu Jie, Zhou Jia, Zheng Zemin
2021, 51(3): 216-227. doi: 10.52396/JUST-2021-0053
Correctly identifying the subgroups in a heterogeneous population has gained increasing popularity in modern big data applications since studying the heterogeneous effect can eliminate the impact of individual differences and make the estimation results more accurate. Despite the fast growing literature, most existing methods mainly focus on the heterogeneous univariate regression and how to precisely identify subgroups in face of multiple responses remains unclear. Here, we develop a new methodology for heterogeneous multi-response regression via a concave pairwise fusion approach, which estimates the coefficient matrix and identifies the subgroup structure jointly. Besides, we provide theoretical guarantees for the proposed methodology by establishing the estimation consistency. Our numerical studies demonstrate the effectiveness of the proposed method.
Research Articles:Management Science and Engineering
Quality and inventory decisions in loss-averse distribution channels considering consumer heterogeneity
Zhang Jinxi, He Haonan, Wang Shanyong, Sun Qipeng, Ma Fei, Ma Tianshan
2021, 51(3): 228-245. doi: 10.52396/JUST-2021-0056
In this paper, we examine firms’ quality and inventory decisions with consumers who behave heterogeneously not only on the product’s valuation (horizontal) but also on the reference price setting (vertical). Through a three-stage Stackelberg leader-follower model, we derive cost-effective solutions for channel members in two distribution scenarios. Counter-intuitively, the analytical result illustrates that profit-maximizing inventory and quality decisions can be higher when the uncertainty of the market increases because the two-dimensional impacts of market uncertainty on demand are diametrically opposite to each other. Specifically, the vertical uncertainty (difference in reference effects) has a buffering effect on the aggregate market demand, which is further amplified by loss-aversion behaviors. However, the horizontal uncertainty (heterogeneity of consumer valuation) has a promoting effect on the market demand and induces firms to order more. The numerical result further shows that market demand may not inherit the behavioral bias of individual consumers, leading to an inconsistent relationship between the sensitivity of market demand to gain/loss and consumers’ loss-aversion behaviors. Our findings have implications not only for understanding the stochastic market demand with behaviorally biased consumers but also for determining the channel members’ optimal inventory and quality decisions.
An end-to-end multitask method with two targets for high-frequency price movement prediction
Ma Yulian, Cui Wenquan
2021, 51(3): 246-258. doi: 10.52396/JUST-2021-0052
High-frequency price movement prediction is to predict the direction(e.g. up, unchanged or down) of the price change in short time(e.g. one minute). It is challenging to use historical high-frequency transaction data to predict price movement because their relation is noisy, nonlinear and complex. We propose an end-to-end multitask method with two targets to improve high-frequency price movement prediction. Specifically, the proposed method introduces an auxiliary target(high-frequency rate of price change), which is highly related with the main target(high-frequency price movement) and is useful to improve the high-frequency price movement prediction. Moreover, each task has a feature extractor based on recurrent neural network and convolutional neural network to learn the noisy, nonlinear and complex temporal-spatial relation between the historical transaction data and the two targets. Besides, the shared parts and task-specific parts of each task are separated explicitly to alleviate the potential negative transfer caused by the multitask method. Moreover, a gradient balancing approach is adopted to use the close relation between two targets to filter the temporal-spatial dependency learned from the inconsistent noise and retain the dependency learned from the consistent true information to improve the high-frequency price movement prediction. The experimental results on real-world datasets show that the proposed method manages to utilize the highly related auxiliary target to help the feature extractor of the main task to learn the temporal-spatial dependency with more generalization to improve high-frequency price movement prediction. Moreover, the auxiliary target(high-frequency rate of the price change) not only improves the generalization of overall temporal-spatial dependency learned by the whole feature extractor but also improve temporal-spatial dependency learned by the different parts of the feature extractor.