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The purpose of this paper is to study the grey decision model and distance measuring method of general grey number.

First, intuitionistic grey number (IGN) set and an IGN are defined by grey number probability function. Second, each interval grey number in general grey number is represented by an IGN and converts the general grey number into an IGN set. Final, the operation of two general grey numbers is defined as the operation between IGN sets, and the distance measure of the general grey number is given.

Up to now, the method of measuring the distance and the grey decision model of general grey number is established. Thus, the difficult problem for set up decision mode of general grey number has been solved to a certain degree.

The method exposed in this paper can be used to integrate information form a different source. The method that a general grey number converted to a set of IGNs could be extended to the case of grey incidence analysis models, grey prediction models and grey clustering evaluation models, which includes general grey numbers, etc.

The concepts of IGN and IGN set are proposed for the first time in this paper; The operation of two general grey numbers can be defined as the operation between IGN sets. On this basis, the algorithm of IGN, the integration operator of IGN and the distance measure between IGN sets are given.

The purpose of this paper is to study distance measuring and sorting method of general grey number.

First, the concept of generalised grey number based on grey system theory is given in this paper. Second, from the perspective of kernel and degree of greyness of general grey number, the method of measuring the distance of general grey number and its properties are given. At the same time, the concepts of the kernel expectation and the kernel variance of the general grey number are proposed.

Up to now, the method of measuring the distance and sorting of general grey number is established. Thus, the difficult problem for set up sorting of general grey number has been solved to a certain degree.

The method exposed in this paper can be used to integrate information form a different source. Distance measuring and sorting method of general grey number could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers, etc.

The concepts of the kernel expectation and the kernel variance of the general grey number are proposed for the first time in this paper; the novel sorting rules of general grey numbers were also constructed.

Special education in China has lagged behind regular education for many years, however, the past few decades, the government has made considerable efforts to develop and improve the special education system. While the citizens of China have had a generic moral interest in disability since ancient times, the development of special education schools did not occur until American and European missionaries started schools for the visually and hearing impaired in the 19th century. The next major influence in the development of the special education system occurred with China’s Cultural Revolution in 1978. Interestingly, there is not any exclusive legislation on special education but in the 1980s, the government started Learning in Regular Classrooms (LRC), which is China’s version of inclusion. LRC has progressed rapidly the past two decades; however, the quality of instruction is low due to a lack of specialists, a shortage of personnel, inadequate funding, and limited technology as well as other barriers that are delineated in the chapter. The chapter emphasizes the government’s recent efforts in in-service teacher training, the preparation of preservice teachers, working with families, developing community rehabilitation training programs, and implementing evidence-based practices. Special education in China today is at a good place but it has quite a way from the ideal situation.

Digital technologies open up unprecedented opportunities for the Chinese wind power industry to make rapid and comprehensive decisions. However, the relationship between digital technology adoption and radical and incremental innovations has not been empirically assessed. In addition, reconfiguration capability is the ability of firms to transform and respond to changes. How such an organizational capability influences the effectiveness of digital technology adoption is a black box. In response, this study aims to assess the relationship between digital technology adoption and radical and incremental innovations in the Chinese wind power industry and elucidate the moderating role of reconfiguration capability.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2020, this study constructs regression models and validates the hypotheses.

The correlation between digital technology adoption and incremental innovation in the wind power industry in China is significantly positive, but the relationship between digital technology adoption and radical innovation is not significant. In addition, reconfiguration capability significantly enhances the incentive effect of digital technology adoption on incremental innovation.

To the best of the authors’ knowledge, this study is one of the earliest to explore the heterogeneous relationships between digital technology adoption and radical and incremental innovations in emerging economies, advancing the theoretical insights into how digital transformation can foster different categories of technological innovations. Moreover, this study embeds dynamic capability theory into digital transformation research by exploring the boundary conditions for the effectiveness of digital technology adoption from the perspective of organizational dynamic capability, thereby expanding the boundaries of existing knowledge.

This chapter focused on presenting the result of the Delphi study from the questionnaire distributed to the experts. The Delphi technique was used for modelling the construction supply chain management (CSCM) practice in the fourth industrial revolution (4IR) era. The technique was also used to predict the supply chain management's (SCM) possible trends in the construction industry. A total of 15 experts were selected for this study based on their working experience. The Delphi study also validated the gaps (organisational culture and 4IR component) identified from the existing CSCM model. The findings from the Delphi study revealed that organisational culture has a significant impact on the practice of CSCM in the 4IR era. Regarding adopting the 4IR component for the CSCM in Nigeria, the Delphi study revealed that smart management and virtualisation are the most adopted. Unfortunately, the cyber-physical system, the heartbeat of the 4IR, is yet to be fully implemented for CSCM practice in the Nigerian construction industry.

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

This study aims to focus on the authority formation process of Chinese enterprise leaders, with the purpose of finding out how an ordinary newly established firm leader develops into a real top leader and achieves the status of legitimacy in a well-known enterprise.

Based on constructivist grounded theory, this paper investigates the formation mechanism of entrepreneurial authority in China by using the rich data of Liu Chuan-zhi’s leader activities.

In the “evolution” path of authority formation, leaders continually consolidate and improve their authority through two classes of exceptional management activities: “emergency rescue” and “promotion activities”. The successful realization of exceptional management activities benefits from a leader’s management experience accumulation and relationship maintenance with the government. In the “design” path of authority formation, leaders consolidate and improve their authority by exercising their position of power. Leaders’ legitimacy is reflected by making strategic decision and demonstrating discretion of position power. Additionally, passing on an inspiring leader’s thoughts and ideas to an organization’s members is accomplished through the construction of organization culture, institutionalization and convention.

First, the findings are based on only Liu Chuan-zhi’s case. The authors still need more cases to compare and develop the findings and seek theoretical saturation in a broader sense. Second, the qualitative analysis is based on secondary data and future research could consider the introduction of interviews, video and other types of research data.

Under the parallel paths which are “evolution” and “design”, the dynamic leader authority formation model in China is founded.

Noncontrolling large shareholders can reduce the agency problem of executives and can reduce the expropriation or tunneling behavior of controlling shareholders, thereby promoting corporate innovation. However, too many noncontrolling large shareholders may also lead to excessive supervision, thereby inhibiting innovative activities that contribute to the long-term value of the firm. Research to date, however, has not examined the nonlinear impact of noncontrolling large shareholders on corporate innovation. Based on principal–agent theory and the too-much-of-a-good-thing (TMGT) effect, the authors discuss the inverted U-shaped influence of noncontrolling large shareholders on corporate innovation and the moderating effect of industry competition and corporate product diversification on the above relationship.

Based on the empirical data of Chinese listed companies from 2003 to 2017, the authors use the bidirectional fixed effects model to conduct empirical testing and robustness testing of the research hypotheses.

There is an inverted U-shaped relationship between noncontrolling large shareholders and corporate innovation; type I and type II agency costs play a mediating role between noncontrolling large shareholders and corporate innovation. In addition, firm product diversification weakens the inverted U-shaped relationship between noncontrolling large shareholders and corporate innovation, but industry competition has no significant moderating effect on the above relationship.

This research has important implications for policy makers, to better activate corporate innovation vitality, and investors, to better choose investment targets. Specifically, investors and policy makers should be aware that an appropriate increase in larger noncontrolling shareholders can maximize the enthusiasm of firms for innovation and enhance corporate value, but they should also realize that having too many noncontrolling large shareholders may backfire.

This research helps the authors to understand the pros and cons of increasing the number of noncontrolling large shareholders more comprehensively and also helps to understand corporate innovation more comprehensively from a supervisory perspective. In addition, this research also enhances the explanatory and predictive power of the TMGT effect.

The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil.

Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula.

It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value.

The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.