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The stock indexes are an important issue for investors, and in this paper good trading strategies will be aimed to be adopted according to the accurate prediction of the stock indexes to chase high returns.

To avoid the problem of insufficient financial data for daily stock indexes prediction during modeling, a data augmentation method based on time scale transformation (DATT) was introduced. After that, a new deep learning model which combined DATT and NGRU (DATT-nested gated recurrent units (NGRU)) was proposed for stock indexes prediction. The proposed models and their competitive models were used to test the stock indexes prediction and simulated trading in five stock markets of China and the United States.

The experimental results demonstrated that both NGRU and DATT-NGRU outperformed the other recurrent neural network (RNN) models in the daily stock indexes prediction.

A novel RNN with NGRU and data augmentation is proposed. It uses the nested structure to increase the depth of the deep learning model.

This study aims to let researchers sort out the past, look to the future and boost further management research.

This paper takes the exploration of the application of AR in the field of management research as the starting point. Through the combing and induction of AR literature to accurately grasp the essential characteristics of AR, this paper analyzes the application prospects and possible difficulties of AR in the field of management research in China, puts forward specific suggestions and explores the specific path of the transformation of management academic research to practice from the perspective of research methods.

In research methods, empirical research and case studies have become the mainstream research methods, but there is a passive research limitation of “study what happens.” Action research is different from the standpoint of empirical research that is independent of the research object. It no longer simply treats managers as the “object of information acquisition,” but as the subject of participating in the research. Management should be oriented towards the transformation of practice, and action research (AR) that can organically integrate researchers and practitioners is just a “bridge” to break the gap between academia and business circles to establish a cooperative relationship.

This paper takes the exploration of the application of AR in the field of management research as the starting point. Through the combing and induction of AR literature to accurately grasp the essential characteristics of AR, this paper analyzes the application prospects and possible difficulties of AR in the field of management research in China, puts forward specific suggestions and explores the specific path of the transformation of management academic research to practice from the perspective of research methods.

Customer co-creation behaviors significantly affect a firm's performance and sustainable growth. This study tested the mediating role of corporate reputation in the relationship between corporate hypocrisy and two types of customer co-creation behaviors: customer citizenship behavior and customer participation behavior. The study also investigated the moderating effect of self-corporate brand connection on the corporate hypocrisy–corporate reputation relationship and the indirect relationship between corporate hypocrisy and customer co-creation behavior through corporate reputation.

The authors conducted a two-wave research survey with 346 Korean bank customers and tested our hypotheses using PROCESS Macro.

Corporate reputation mediated the relationship between corporate hypocrisy and customer citizenship/participant behavior. The negative effect of corporate hypocrisy on corporate reputation was more pronounced when self-corporate brand connection was high. Self-corporate brand connection further moderated the indirect effect of corporate hypocrisy on customer citizenship/participant behavior through corporate reputation.

The results clearly explain how corporate hypocrisy affects customer co-creation behavior. This study advances corporate hypocrisy and corporate reputation research by proposing and verifying a moderated mediation model.

This paper aims to propose an energetic model parameter calculation method for predicting the materials’ symmetrical static hysteresis loop and asymmetrical minor loop to improve the accuracy of electromagnetic analysis of equipment.

For predicting the symmetrical static hysteresis loop, this paper deduces the functional relationship between magnetic flux density and energetic model parameters based on the materials’ magnetization mechanism. It realizes the efficient and accurate symmetrical static hysteresis loop prediction under different magnetizations. For predicting the asymmetrical minor loop, a new algorithm is proposed that updates the energetic model parameters of the asymmetrical minor loop to consider the return-point memory effect.

The comparison of simulation and experimental results verifies that the proposed parameters calculation method has high accuracy and strong universality.

The proposed parameter calculation method improves the existing parameter calculation method’s problem of relying on too much experimental data and inaccuracy. Consequently, the presented work facilitates the application of the finite element electromagnetic field analysis method coupling the hysteresis model.

This paper aims to investigate the relationship between exchange ideology and employee creativity based on the social exchange perspective. It also attempts to examine the mediating role of perceived shared leadership and the moderating role of vertical moral leadership.

Multilevel and multisource data were collected from 56 research and development (R&D) teams with 306 employees. Hypotheses were tested with multilevel path analysis.

The authors found that exchange ideology was negatively related to both perceived shared leadership and employee creativity, and perceived shared leadership mediated the relationship between exchange ideology and employee creativity. Moreover, we revealed that vertical moral leadership buffered the negative relationship between employee exchange ideology and perceived shared leadership and also the indirect effect of exchange ideology on employee creativity via perceived shared leadership.

Organizations should select employees with a relatively weak exchange ideology when forming teams to conduct creative tasks. Moreover, team leaders should make great efforts to facilitate the development of shared leadership among team members while to be a moral leader.

This study extends creativity literature by investigating the effect of exchange ideology on employee creativity. It also sheds lights on leadership research by examining the mediating role of perceived shared leadership and the moderating role of vertical moral leadership.

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.

This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.

Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.

The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.

The purpose of this paper is to analyze the heterogeneity of regional grain production distribution in China, by examining the regional heterogeneity of absolute and relative changes in grain planting acreage, and explain it in terms of increasing labor costs and difficulties in agricultural inputs adjustment.

The study uses data from official statistical yearbooks and the satellite remote sensing image data of Landsat TM 30 m. Multivariate analysis is conducted to examine the effect of labor cost, difficulty in replacing agricultural input factors and other factors underpinning changes in grain acreage and grain structure adjustment.

The heterogeneity of changes in grain acreage and proportion of arable area for grain production are mainly determined using the labor cost and difficulties in the replacement of agricultural input factors.

To the best of the authors’ knowledge, this study is the first to systematically analyze the heterogeneity in restructuring grain production at provincial level and its causes. The results not only provide evidence of grain production restructuring at regional level, but also contribute to the understanding of the law of structural change in agricultural production.

This paper aims to propose and establish a set of new benchmark models to investigate and confidently validate the modeling and prediction of total stray-field loss inside magnetic and non-magnetic components under harmonics-direct current (HDC) hybrid excitations. As a new member-set (P21^e) of the testing electromagnetic analysis methods Problem 21 Family, the focus is on efficient analysis methods and accurate material property modeling under complex excitations.

This P21^e-based benchmarking covers the design of new benchmark models with magnetic flux compensation, the establishment of a new benchmark measurement system with HDC hybrid excitation, the formulation of the testing program (such as defined Cases I–V) and the measurement and prediction of material properties under HDC hybrid excitations, to test electromagnetic analysis methods and finite element (FE) computation models and investigate the electromagnetic behavior of typical magnetic and electromagnetic shields in electrical equipment.

The updated Problem 21 Family (V.2021) can now be used to investigate and validate the total power loss and the different shielding performance of magnetic and electromagnetic shields under various HDC hybrid excitations, including the different spatial distributions of the same excitation parameters. The new member-set (P21^e) with magnetic flux compensation can experimentally determine the total power loss inside the load-component, which helps to validate the numerical modeling and simulation with confidence. The additional iron loss inside the laminated sheets caused by the magnetic flux normal to the laminations must be correctly modeled and predicted during the design and analysis. It is also observed that the magnetic properties (B27R090) measured in the rolling and transverse directions with different direct current (DC) biasing magnetic field are quite different from each other.

The future benchmarking target is to study the effects of stronger HDC hybrid excitations on the internal loss behavior and the microstructure of magnetic load components.

This paper proposes a new extension of Problem 21 Family (1993–2021) with the upgraded excitation, involving multi-harmonics and DC bias. The alternating current (AC) and DC excitation can be applied at the two sides of the model’s load-component to avoid the adverse impact on the AC and DC power supply and investigate the effect of different AC and DC hybrid patterns on the total loss inside the load-component. The overall effectiveness of numerical modeling and simulation is highlighted and achieved via combining the efficient electromagnetic analysis methods and solvers, the reliable material property modeling and prediction under complex excitations and the precise FE computation model using partition processing. The outcome of this project will be beneficial to large-scale and high-performance numerical modeling.

Finance is crucial to boosting agricultural development in developing countries. This paper aims to investigate the effects of rural formal and informal financial access on agricultural technical efficiency (TE) in China.

Based on the survey data of demonstrative family farms in Langxi county, Anhui province and Wuhan city, Hubei province in central China in 2017, this research assesses agricultural TE by using a three-stage DEA model. It adopts the tobit model to evaluate the effects of formal and informal financial access on TE, and to explore the heterogeneous effects by types, management states and scales. It uses the OLS regression and PSM method to check the robustness, and applies the IV-Tobit method to solve the endogeneity. The authors apply the mediation effect model to explore the channels through which financial access impacts TE.

Family farms' average TE reaches 13.9%, which shows much room for improvement under the given technical conditions and constant inputs. The research confirms the advantage of formal financial access in raising TE relative to informal financial access. The heterogeneous analysis documents more prominent effects of formal financial access on enhancing TE of aquaculture, hybrid, demonstration and large farms. The mediating effect model reveals that the enhancing TE effect of formal financial access derives from improved machinery investment and family labor division rather than land circulation.

The research clarifies finance into formal and informal finance. The results have considerable policy implications for rural financial policies in China.