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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.

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.

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.

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.