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The purpose of this paper is to propose a multi-scale extended grey target decision method for dealing with multi-attribute decision-making problems with interval grey numbers whose value distribution information is asymmetrical.

First, the whitenization weight function (WWF) was adopted to show the value distribution information of interval grey numbers. The definitions of kernel, degree of greyness, relative kernel and whitenization standard deviation of interval grey numbers were given based on the WWF. Then, the relative kernel grey target and whitenization standard deviation grey target were constructed to take full advantage of the owned decision information. Finally, the relative bull’s-eye coefficient was proposed to rank the preference order of all alternatives.

The relative bull’s-eye coefficient reflects the influence of the decision information on decision results with respect to the mean level and value distribution of attribute values. Thus, the decision-maker could set the return and risk adjustment coefficient according to their preferences and select the optimal alternative with a high expected return and low risk.

The paper considers the valve distribution information of interval grey numbers, and a novel definition for kernels, degrees of greyness, relative kernels and whitenization standard deviations, which are given based on the WWF. The paper not only considers the influence of mean levels of decision information over decision results, but also takes the value distribution information into account.

Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

The purpose of this paper is to propose the grey target decision method based on three-parameter interval grey number for dealing with multi-attribute decision-making problems under uncertain environment.

First, the kernel and ranking method of three-parameter interval grey number are defined, which is the basis of determining the positive and negative bull’s-eye. Next, a new distance measure of three-parameter interval grey number is defined in view of the importance of the “center of gravity” point. Furthermore, a new comprehensive bull’s-eye distance is proposed based on the kernel which integrates the distance between different attributes to the positive and negative bull’s-eye. Then attribute weights are obtained by comprehensive bull’s-eye distance minimum and grey entropy maximization.

The paper provides a grey target decision method based on three-parameter interval grey number and example analysis shows that the method proposed in this paper is more reasonable and effective.

If we have a better understanding of the distribution characteristics of three-parameter interval grey number, it is possible to have a more reasonable measure of the distance of three-parameter interval grey number.

The paper provides a grey target decision method, which can help decision maker deal with multi-attribute decision-making problems under uncertain environment.

This paper proposed the kernel and ranking method of three-parameter interval grey number, and defined a new distance measure of three-parameter interval grey number and proposed a new comprehensive bull’s-eye distance, Furthermore, this paper structured a grey target decision method based on three-parameter interval grey number.

The purpose of this paper is to evaluate doctoral candidates’ innovative ability tendency.

This study uses the theory of gray target contribution to analyze the influence degree of doctoral candidates’ individual personality factor toward their innovative ability and calculate gray impact quantitative values.

Based on the theory of contribution degree of gray target, a nine-factor model of innovative personality of doctoral candidates is built. IP=f (B, H, G, Q1, Q2, A, I, F, O), (therein: B – intelligence, H – social boldness, G – perseverance, Q1 – experimental, Q2 – independence, A – gregariousness, I – sensibility, F – excitability, O – anxiety).

This study based on gray target contribution theory builds nine-factor doctoral candidates’ innovative personality model to test the innovative ability tendency of doctoral candidates, which makes cultivating units, mentors and doctoral candidates to know their innovative ability tendency well, perfecting their own knowledge structure in time, effectively improving their innovative ability. The system can also be applied to the work of doctoral candidates as a reference tool to evaluate the innovative ability of applicants.

This study quantitatively evaluates the influence of doctoral candidates’ personality index on the tendency of doctoral candidates’ innovative ability.

The purpose of this paper is to analyze the reliability and validity of doctoral candidates’ innovative personality model.

Based on doctoral candidates’ innovative personality model, this study took the best correlation and the worst correlation into account to predict and demonstrate their innovative ability tendencies. Matlab R2016a, a program of software programming, was used to calculate the contribution degree of each personality factor of doctoral candidates to their innovative ability tendencies.

The reliability and validity of doctoral candidates’ innovative personality model based on grey target theory have been verified, and the prediction for doctoral candidates’ innovative ability tendencies can be realized on the basis of this model.

Scientific and reasonable doctoral candidates’ innovative personality model can play a good guiding role, and its research results have certain practical significance for selecting innovative doctoral candidates, ensuring the training quality of doctoral candidates and cultivating the innovative ability of doctoral candidates. It can be promoted and applied on the basis of its trial operation in Jiangsu.

With regard to the relative degree of the influence of doctoral candidates’ individual personality factors, previous researchers seldom carried out the quantitative research. In this paper, the author sought a quantitative method to describe the degree of such influence and constructed the doctoral candidates’ innovative personality model based on grey target decision making. This study took the positive and negative off-target distance into account and demonstrated the rationality and validity of doctoral candidates’ innovative personality model.

The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number.

First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle.

The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality.

If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function.

The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment.

The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

Brand managers in packaged goods firms are under pressure to increase or maintain high sales promotion spending at the expense of media advertising. This study investigates the antecedents and outcomes of brand managers’ advertising and sales promotion budget allocations by adopting a bounded rationality perspective. Based on survey data collected from 165 brand managers in the USA, higher advertising (vs sales promotion) allocations are associated with: single, relatively high priced brands in the early phases of the product life cycle; and more experienced brand managers who are subject to less retail influence. Also, brands with higher budget allocations to advertising, relative to sales promotion, tend to have more favorable consumer attitudes, stronger brand equity, and higher market share increases and profits. Managerial implications and areas for future study are discussed.

During the service period of communication satellite systems, their performance is often degraded due to the depletion mechanism. In this paper, the grey system theory is applied to the multi-state system effectiveness evaluation and the grey Lz-transformation ADC (availability, dependability and capability) effectiveness evaluation model is constructed to address the characteristics of the communication satellite system such as different constituent subsystems, numerous states and the inaccuracy and insufficiency of data.

The model is based on the ADC effectiveness evaluation method, combined with the Lz transformation and uses the definite weighted function of the three-parameter interval grey number as a bridge to incorporate the possibility of system performance being greater than the task demand into the effectiveness solution algorithm. At the same time, using MATLAB (Matrix laboratory) to solve each state probability, the same performance level in the Lz transform is combined. Then, the system effectiveness is obtained by Python.

The results show that the G-Lz-ADC model constructed in this paper can accurately evaluate the effectiveness of static/dynamic systems and certain/uncertain system and also has better applicability in evaluating the effectiveness of the multi-state complex system.

The G-Lz-ADC effectiveness evaluation model constructed in this paper can effectively reduce the complexity of traditional effectiveness evaluation models by combining the same performance levels in the Lz-transform and solving the effectiveness of the system with the help of computer programming, providing a new method for the effectiveness evaluation of the complex MSS. At the same time, the weaknesses of the system can be identified, providing a theoretical basis for improving the system’s effectiveness.

The possibility solution method based on the definite weighted function comparing the two three-parameter interval grey numbers is constructed, which compensates for the traditional calculation of the probability based on numerical values and subjective preferences of decision-makers. Meanwhile, the effectiveness evaluation model integrates the basic theories of three-parameter interval grey number and its definite weighted function, Grey−Markov, grey universal generating function (GUGF), grey multi-state system (GMSS), etc., which is an innovative method to solve the effectiveness of a multi-state instantaneous communication satellite system.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.