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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.

To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results can also provide references for railway departments to plan railway operation lines reasonably and efficiently.

This paper intends to establish a seasonal cycle first order univariate grey model (GM(1,1) model) combing with a seasonal index. GM (1,1) is termed as the trend equation to fit the railway passenger volume in China from 2014 to 2018. The railway passenger volume in 2019 is used as the experimental data to verify the forecasting effect of the proposed model. The forecasting results of the seasonal cycle GM (1,1) model are compared with the traditional GM (1,1) model, seasonal grey model (SGM(1,1)), Seasonal Autoregressive Integrated Moving Average (SARIMA) model, moving average method and exponential smoothing method. Finally, the authors forecast the railway passenger volume from 2020 to 2022.

The quarterly data of national railway passenger volume have a clear tendency of cyclical fluctuations and show an annual growth trend. According to the comparison of the modeling results, the authors know that the seasonal cycle GM (1,1) model has the best prediction effect with the mean absolute percentage error of 1.32%. It is much better than the other models, reflecting the feasibility of the proposed model.

As the previous grey prediction model could not solve the series prediction problem with seasonal fluctuation, and there are few research studies on quarterly railway passenger volume forecasting, GM (1,1) model is taken as the trend equation and combined with the seasonal index to construct a combination forecasting model for accurate forecasting results in this study. Besides, considering the impact of the epidemic on passenger volume, the authors introduce a disturbance factor to deal with the forecasting results in 2020, making the modeling results more scientific, practical and referential.

Due to social transformation in China, more than 100,000,000 people are migrating within the country. Many parents are forced to leave their children behind when they migrate. In 2008, 58,000,000 children were living as left‐behind children, mainly in the rural parts of China (Zhang, 2009).Migration and its accompanying stressors may affect the mental health of the left‐behind children. This unique literature review of Chinese literature summarises the present state of knowledge and reviews the influential factors. Possible approaches to intervention and system reforms are discussed.A literature review was performed of published studies between 2001 and 2008. Databases used were Fujian Medical University Library Interface, Chinese National Knowledge Infrastructure, Wanfang Data, and VIP Information. The Chinese word for ‘left‐behind’ was used as a key word. Books, book chapters, monographs and studies on caring were searched electronically and by hand. Altogether, 53 items were found, discussed and grouped together. Migration affected the mental health of the left‐behind children in a passive way, especially their emotions and social behaviour.There is still controversy over how serious mental health problems are among children who have been left behind. Life events, personality, coping strategies and social suppor t can be regarded as four main factors that are predictive of mental health, which provides theoretical guidance for intervention. Suppor t and prevention of mental health problems in schools, in families and in primary care should be developed and studied.

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

Although green logistics has become a new focus of cooperation between government and enterprises under environmental constraints, how local governments formulate subsidy policies to effectively guide the green transformation of regional logistics and how to facilitate the reasonable cost-sharing are rather critical. This paper will deeply explore the dynamic process of the tripartite participation (government, platform, and logistics enterprises) in the selection of regional green logistics strategy, and reveal the evolutionary game relationship of the three parties.

To explore the dynamics involving the government, platform and logistics enterprises for the green logistic transformation, and reveal the evolutionary gaming among the three parties, based on the bounded rationality premise, this study constructs the tripartite asymmetric evolutionary game models, uses the stability theorem of differential equation to explore the evolution and stability strategy of the system in different cases and explicates the paths of influence on the tripartite behaviors via simulations.

Results of this study indicate that there exist stable equilibrium strategies among the three parties regarding the regional green logistics, and they are affected by different factors. The government's subsidy, subsidy intensity and the platform's cost-sharing proportion can generate positive effects, but the latter two can also impact negatively beyond the effective ranges. The findings provide a theoretical basis for local governments, platforms and logistics enterprises to formulate justifiable subsidy intensity and determine reasonable sharing proportion.

Firstly, considering the significant relevance of local government, it is included in the evolution model, and the tripartite game (among government, platform and enterprises) is explored; Secondly, by comparing the equilibrium results under different game conditions, this paper analyzes the evolution of each party's game strategy to achieve the optimal return under bounded rationality and the important factors determining the strategic selection; Finally, the key factor of platform cost sharing is involved, and to what extent the change of platform cost sharing ratio will influence the systematic stability is explored.

This study aims to reveal the empirical linkage between tourists’ perspectives and attitudes towards disaster ruins and dark tourism by attesting influence relationships between disaster memorials perception, dark tourism evaluation, as well as heritage protection and tourism development intention.

Partial least squares structural equation modeling analysis was used on a sample of 413 valid visitor questionnaires collected at the 5·12 Wenchuan Earthquake Memorial Museum, Sichuan Province, China.

Disaster memorials perception positively influences positive evaluation of dark tourism, heritage protection intention and tourism development intention, while negatively influencing negative evaluation of dark tourism. Furthermore, positive evaluation of dark tourism and heritage protection intention positively affect tourism development intention. In addition, prior knowledge is a significant moderator in the research model.

This study applied the stimulus-organism-response framework and social exchange theory to predict tourists’ behavioral intention toward disaster memorials, providing valuable insights to dark tourism research. It illuminates tourists’ psychological and behavioral characteristics at natural disaster sites and deepens research on the human–nature relationship from the disaster perspective.

本研究试图通过验证自然灾难遗址地游客感知、旅游评价、遗产保护意愿与旅游开发意愿之间的影响关系, 以揭示游客对灾难遗址和黑色旅游的感知及态度之间的隐秘逻辑。

采用偏最小二乘法结构方程模型, 对在中国四川省5·12汶川特大地震纪念馆收集的413份有效游客问卷进行分析。

灾难遗址感知正向影响黑色旅游积极评价、遗产保护意愿和旅游开发意愿, 而负向影响黑色旅游消极评价。同时, 黑色旅游积极评价和遗产保护意愿均显著正向影响旅游开发意愿。此外, 游客的先验知识在研究模型中起着重要的调节作用。

本研究运用“刺激-机体-反应”研究框架预测了旅游者对自然灾难遗址地的行为意向, 深化了黑色旅游研究, 拓宽了S-O-R理论的适用范围。

Este estudio revela el vínculo empírico entre las perspectivas y las actitudes de los turistas hacia las ruinas de catástrofes y el Turismo oscuro, mostrando las relaciones de influencia entre la percepción de los monumentos conmemorativos de catástrofes, la evaluación del turismo oscuro, así como la protección del patrimonio y la intención de desarrollo turístico.

Se empleó un análisis de modelización de ecuaciones estructurales por mínimos cuadrados parciales en una muestra de 413 cuestionarios válidos de visitantes recogidos en el 5·12 Museo Conmemorativo del Terremoto de Wenchuan, Sichuan, China.

La percepción de los monumentos conmemorativos de las catástrofes influye positivamente en las evaluaciones positivas del turismo oscuro, la intención de protección del patrimonio y la intención de desarrollo turístico, mientras que influye negativamente en las evaluaciones negativas del turismo oscuro. Además, las evaluaciones positivas del turismo oscuro y la intención de protección del patrimonio influyen positivamente en la intención de desarrollo turístico. Además, el conocimiento previo moderadora significativamente el modelo de investigación.

Este estudio aplica el marco teórico estímulo-organismo-respuesta (E-O-R) y la teoría del intercambio social para predecir las intenciones de comportamiento de los turistas hacia los monumentos conmemorativos de catástrofes, proporcionando valiosas ideas para el estudio del turismo oscuro. Clarifica las características psicológicas y conductuales de los turistas en los lugares de catástrofes naturales y profundiza en el estudio de la relación entre el ser humano y la naturaleza desde la perspectiva de las catástrofes.

This study aims to propose an improved affine interval truncation algorithm to restrain interval extension for interval function.

To reduce the occurrence times of related variables in interval function, the processing method of interval operation sequence is proposed.

The interval variable is evenly divided into several subintervals based on correlation analysis of interval variables. The interval function value is modified by the interval truncation method to restrain larger estimation of interval operation results.

Through several uncertain displacement response engineering examples, the effectiveness and applicability of the proposed algorithm are verified by comparing with interval method and optimization algorithm.