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Given the significance of innovation in enabling firms to maintain a long-term competitive edge and secure excess profits, this paper aims to investigate whether and how stakeholders’ attention to innovation (SATI) influences corporate innovation.

This paper introduces a novel variable, SATI, which is achieved by segmenting stakeholders’ attention into two categories: attention to innovation and attention to other facets, using textual analysis methods. Subsequently, this paper empirically examines the influence of SATI on corporate innovation.

This paper finds that SATI positively affects corporate innovation input, and the result remains true after addressing possible endogeneity issues using instrumental variable regression. Furthermore, the positive effect of SATI on corporate innovation is stronger in firms facing greater financing constraints, thus verifying the financing constraints hypothesis. The positive effect is also stronger in firms with lower risk-taking levels, thus confirming the innovation failure tolerance hypothesis. Further analysis suggests that SATI increases both corporate innovation output and efficiency, thus ruling out the catering hypothesis.

This paper highlights the importance of SATI in driving corporate innovation. It enriches the literature on the repercussions of stakeholders’ attention and determinants of corporate innovation. In addition, it provides practical suggestions for further implementing China’s national innovation-driven development strategy.

The purpose of this paper is to model the announcement returns of merging firms based on managerial overconfidence about merger synergy.

The paper applies continuous‐time real options techniques and game theoretic concepts. Managerial overconfidence and strategic interaction between the bidder and the target are incorporated into the model.

This model implies that: abnormal returns to bidding shareholders will be negative with a high degree of managerial overconfidence; combined returns to shareholders are usually positive; and both the bidder's and the target's abnormal returns are related to industry characteristics, the degree of managerial overconfidence, and the way merger synergies are divided.

This paper, for the first time, reconciles theoretically the following stylized facts: combined returns to shareholders are usually positive; and returns to the acquirer are, on average, not positive. In addition, the model generates new predictions relating these returns to industry characteristics and the degree of managerial overconfidence.

The purpose of this study is to explore whether information technology (IT) integration capability and data sharing can improve project management performance in China’s construction industry under the background of global informatization. Moreover, the authors explore the moderating role of relational governance between IT integration capability and data sharing.

A theoretical model based on the research hypotheses proposed in this study was developed, and a questionnaire survey was conducted with 205 professionals. The data collected were analyzed by the structural equation modeling (SEM) technique.

The results indicate that IT integration capability has a significant and positive impact on project management performance and data sharing. Moreover, data sharing has a significant and positive impact on project management performance, and it plays a mediating role between IT integration capability and project management performance. In addition, relational governance significantly influences the mediating effect of data sharing.

The data used in this study is from Chinese scenarios, so the research conclusions and application effects based on this are bound to have certain regional limitations. So, a larger sample size from other countries could be selected to test the model. Besides, there are many factors that affect project management performance improving, and the theoretical model proposed in this study may not be fully considered. Therefore, follow-up researchers can consider bringing more suitable variables into their research studies, so that the theoretical research studies can be more in line with the actual project management practice.

This research’s value is as follows: Firstly, this paper broadens the understanding of how IT integration capability, data sharing and relational governance affects project management performance and enriches the literature in the construction management field under the background of global informatization. Secondly, this research provides a detailed governance solution to improve project management performance.

For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure. However, how to find the useful rules or knowledge hidden in the data is very important and challengeable. Rule extraction methods are very useful in mining the important and heuristic knowledge hidden in the original high-dimensional data. It can help us to construct predictive models with few attributes of the data so as to provide valuable model interpretability and less training times.

In this paper, a novel rule extraction method with the application of biclustering algorithm is proposed.

To choose the most significant biclusters from the huge number of detected biclusters, a specially modified information entropy calculation method is also provided. It will be shown that all of the important knowledge is in practice hidden in these biclusters.

The novelty of the new method lies in the detected biclusters can be conveniently translated into if-then rules. It provides an intuitively explainable and comprehensive approach to extract rules from high-dimensional data while keeping high classification accuracy.

The purpose of this study is to modify guar gum (GG) into guar gum acetate (GGA) and phthaloyl guar gum (PHGG) by transesterification and phthaloylation, respectively.

GG has been modified into GGA through transesterification reaction between GG and vinyl acetate and PHGG through esterification reaction with phthalic anhydride. The modified GG was characterized by solubility test, Fourier-transform infra-red (FTIR) spectroscopy, proton nuclear magnetic resonance (¹H NMR) spectroscopy, X-ray diffractometry (XRD) and thermogravimetric analysis. Swelling properties of GGA and PHGG hydrogels in water were evaluated.

These two types of modified GG have better solubility such as in dimethyl sulfoxide and N,N-dimethylformamide but no true organosolubility was achieved. The modifications were confirmed through FTIR with new absorption peaks at 1,733 cm⁻¹ for GGA and 1,709 cm⁻¹ for PHGG coupled with observed substitution peaks at 1.80 to 2.20 ppm and 7.40 to 7.90 ppm, respectively, from ¹H NMR spectroscopies. XRD revealed both GGA and PHGG are less crystalline than native GG. GGA was found to be more thermally stable than native GG, whereas PHGG was slightly less thermally stable than native GG. The swelling property in distilled water for native GG, PHGG and GGA was 918.43 ± 46.62%, 537.04 ± 2.87% and 393.04 ± 13.42%, respectively.

The GGA and PHGG hydrogels are expected to be useful for biomedical fields such as tissue engineering and drug-delivery.

Modifications of native GG into GGA using vinyl acetate and PHGG using phthalic anhydride are novel.

The purpose of this paper is to present a new plan approach for optimal allocation water resources in social‐economic‐environmental complex system in order to achieve human and nature coordinated development.

By integrating the system dynamics (SD) and multi‐objective programming (MOP), the new approach which is termed SD‐MOP model is proposed. The model is characterized by fully reflecting the initial trends of the system development, accurately explaining both of the structure and function of the system, objectively finding the sensible points of the system, and achieving the optimum solutions of the model, the according the solutions the optimal plan can be designed according practical situation.

By applying SD‐MOP integrated model, the designed planning proposal can be guaranteed operable, available, and optimal level.

SD‐MOP integrated model is a very useful support tool in optimal decision making.

The new planning approach of SD‐MOP integrated model can be used in regional resources planning, especially in formulating sustainable development strategies. In addition, the model can be used to estimate the trends of the system development when the planning program has been implemented.

This paper aims to investigate the corrosion kinetics and corrosion behavior of NdFeB magnets with the addition of heavy rare earth dysprosium (Dy) for its inhibitory activity on poor corrosion resistance of NdFeB magnets.

To study the effect of dysprosium addition on corrosion behavior of NdFeB magnets and investigate its mechanism, potentiodynamic polarization, scanning electron microscopy (SEM), electrochemical impedance, energy dispersion spectrum (EDS) and scanning Kelvin probe force microscopy (SKPFM) were applied in the research. Besides, microstructures were observed by SEM equipped with EDS. Atomic force microscopy was introduced to analyze the morphology, potential image as well as the contact potential difference. The SKPFM mapping scan was applied to obtain the contact potential around Nd-rich phase at 0.1 Hz. The magnets were detected via X-ray diffraction.

Substitution of Nd with Dy led to improvement of corrosion resistance and reduced the potential difference between matrix and Nd-rich phase. Corrosion resistance is Nd-rich phase < the void < metal matrix; maximum potential difference between matrix and Nd-rich phase of Dy = 0, Dy = 3 and Dy = 6 Wt.% is 411.3, 279.4 and 255.8 mV, respectively. The corrosion rate of NdFeB magnet with 6 Wt.% Dy is about 67% of that without Dy at steady corrosion stage. The addition of Dy markedly enhanced the corrosion resistance of NdFeB magnets.

This research innovatively investigates the effect of adding heavy rare earth Dy to NdFeB permanent magnets on magnetic properties, as well as their effects on microstructure, phase structure and most importantly on corrosion resistance. Most scholars are studying the effect of element addition on magnetic properties but not on corrosion resistance. This paper creatively fills this research gap. NdFeB magnets are applied in smart cars, robotics, AI intelligence, etc. The in-depth research on corrosion resistance by adding heavy rare earths has made significant and outstanding contributions to promoting the rapid development of the rare earth industry.

The purpose of this paper is to seek an efficient method to tackle the energy provision problem for smart grid with sparse constraints and distributed energy and storage devices.

A complex smart grid is first studied, in which sparse constraints and the complex make-up of different energy consumption due to the integration of distributed energy and storage devices and the emergence of multisellers are discussed. Then, a real-time pricing scheme is formulated to tackle the demand response based on sparse bilevel programming. And then, a bilevel genetic algorithm (BGA) is further designed. Finally, simulations are conducted to evaluate the performance of the proposed approach.

The considered situation is widespread in practice, and meanwhile, the other cases including traditional model without the sparse constraints can be seen as its extensions. The BGA based on sparse bilevel programming has advantages of “no need of convexity of the model.” Moreover, it is feasible without the need to disclose the private information to others; therefore, privacies are protected and system scalability is kept. Simulation results validate the proposed approach has good performance in maximizing social welfare and balancing system energy distribution.

In this paper, the authors consider the sparse constraints due to the fact that each user can only choose limited utility companies per time slot. In reality, there exist some other sparse cases, which deserve further study in the future.

To the best of the authors’ knowledge, this is one of the very first studies to address pricing problems for the smart grid with consideration of sparse constraints and integration of distributed energy and storage devices.

This paper aims to obtain optimal specialization mode and level for complex network or system structures. In the e-commerce system, this paper studies the changes of each transaction subject in the process of ecological structure based on the income level of each transaction subject.

This paper aims to research the change of transaction efficiency evolution process of intermediaries. With the improvement of transaction efficiency, intermediaries interact with other transaction subjects at given modes in e-commerce systems. This paper analyzes the relationship between the factors of production and trade and explains the quantitative relationship between them in the form of mathematical modeling. An evolution simulation framework is established to elaborate the simulation process and method of crowd network in e-commerce ecosystem and then sets up the simulation experiment.

During simulation processes, the changes of data are observed and analyzed to obtain the optimal evolution paths and specialization modes. Furthermore, this paper provides solid supports for the research of the quantitative analysis of ecological structure evolutions.

Evolution simulation of ecological structure is first proposed in the topic of crowd network. It is with the aid of the concept of ecology, the theory and method, simulation of complex network structure and system structure. This paper analyses and researches the evolution process of optimal specialization modes and intelligent level of crowd networks with transaction efficiency changing. The ecological structure optimal evolution paths can be obtained by trend of simulations.

This study aims to explore an interpersonal predictor of coworkers-directed knowledge hiding behavior – the leader–member exchange social comparison (LMXSC). This study integrates leader–member exchange literature with social comparison theory to hypothesize that an individual’s upward LMXSC is positively correlated with coworkers-directed knowledge hiding and that an individual’s feelings of envy are mediated by the relationship between upward LMXSC and coworkers-directed knowledge hiding behavior. Also, this study proposes two-way and three-way interaction patterns of goal interdependence, which can influence LMXSC–envy relationships.

Two independent studies are conducted to test the hypothesized relationships. In Study 1, the authors collected multi-wave data from a large public sector university in China (N = 1,131). The authors then replicated the Study 1 findings by collecting multi-source and multi-wave data from a telecom company based in China (n = 379).

The authors found support across both studies for the idea that upward LMXSC is a possible interpersonal predictor of coworkers-directed knowledge hiding behavior. More specifically, it was found that feelings of envy ensue from upward LMXSC, resulting in further coworkers-directed knowledge hiding behavior. Further, this study shows that the influence of upward LMXSC on knowledge hiding behavior via feelings of envy was weaker (stronger) when employees have high (low) cooperative goal interdependence with coworkers, respectively, and when employees have low (high) competitive goal interdependence with the coworkers, respectively.

This study extends current knowledge management literature by introducing LMXSC as an interpersonal predictor of coworkers-directed knowledge hiding behavior. This will help practitioners to curb such counterproductive behavior.