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The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.

Blown up theory is very important in modern forecasting science, and will result in revolution not only in forecasting theories but also in applied theories and applied methods. Moreover, the blown‐up theory will involve re‐thinking and re‐formulation of some concepts in traditional theories. This article is a record of dialogue between Professor OuYang and the author on some important issues. It is believed that this record will not only benefit us greatly, but also be inductive for young generations in developing their way of thinking and research directions.

Since the present university leading cadre capability evaluations are mainly static, there is a lack of evaluation methods to address dynamic and multi‐scale‐based situations. Some important factors to address people's performances, such as the developing trends and potentialities are considered. The purpose of this paper is to attempt to propose a dynamic evaluation model based on multivariate delay connection number.

First, evaluation results of previous periods are taken into the current period and values of uncertain numbers are revised. Next, a dynamic evaluation model is built for university leading cadre. Last, a numerical example is used to prove its feasibility and effectiveness.

This paper promotes a corrected equal portion value method of uncertain numbers i1(τ), … ,in(τ) from the adjacent two periods to multi periods, and builds a dynamic evaluation model, which proved simple‐structured and easy to apply.

The new model is applied in the evaluation of university leading cadre, and could give a more comprehensive, dynamic, scientific analysis for evaluation by model application.

The paper develops a novel evaluation model based on a multivariate delay connection number, which expands traditional methods from a static situation to a dynamic and multi‐scale‐based situation.

The purpose of this paper is to explore the structure of the concept of customer‐perceived quality (CPQ) in electronic commerce (e‐commerce).

The study applies the methodology of concept mapping to data obtained from online and offline focus groups. Following a series of structured conceptualization tasks, the data were analyzed using multidimensional scaling and hierarchical cluster analysis to establish a conceptual construct of e‐commerce CPQ.

The proposed conceptual construct consists of six dimensions: outcome quality; consumer service; process controllability; ease of use; information quality; and web site design. The study finds that online consumers attach more importance to quality attributes associated with outcome quality and consumer service than to attributes associated with web transactions.

The sample should be extended to facilitate the generalization of the findings from this research.

This paper identifies a three‐level structure for e‐commerce quality as perceived by consumers. The study offers practical insights to online retailers in providing superior service.

The purpose of this paper is to introduce a quantitative method for assisting contractors to select appropriate projects for bidding by considering multiple attributes and integrating decision group member opinions.

The fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is used to help contractors make decision on project selection and the linguistic terms are defined for representing the triangular fuzzy numbers for ratings of alternatives and weights of criteria.

The selection of appropriate projects for bidding is a multiple attribute group decision‐making exercise. In a real decision process, there are many uncertainties and ambiguities, and time limitations mean that decision makers cannot always make precise judgments. The numerical example demonstrates that the fuzzy TOPSIS approach can be used to simulate the decision process in project selection, and the results provide contractors with valuable insight into the project selection problem.

Selecting appropriate projects for bidding is to use a contractor's limited resources more efficiently and increase the probability of winning contracts. Therefore, there is a need for a quantitative method to help contractors make better decision on project selection. That leads to the formulation of this paper. The fuzzy TOPSIS method can assist contractors to make better decisions in bidding.

This study aims to propose a new variable stiffness robot joint (VSR-joint) for operating safely. More and more variable stiffness actuators are being designed and implemented because of their ability to minimize large forces due to shocks, to safely interact with the user and their ability to store and release energy in passive elastic elements.

The design of VSR-joint is compact and integrated highly and the operating is simply. The mechanics, the principle of operation and the model of the VSR-joint are proposed. The principle of operation of VSR-joint is based on a lever arm mechanism with a continuously regulated pivot point. The VSR-joint features a highly dynamic stiffness adjustment along with a mechanically programmable system behavior. This allows an easy adaption to a big variety of tasks.

Preliminary results are presented to demonstrate the fast stiffness regulation response and the wide range of stiffness achieved by the proposed VSR-joint design.

In this paper, a new variable stiffness joint is proposed through changing the cantilever arm to change the performance of the elastic element, which is compact, small size and simple adjustment.

In operational tropical cyclone (TC) forecasting practice, there are usually many TC track guidances available from various official sources. When they do not converge, the guidances need to be ensembled by systematic approaches to formulate the best possible track as an official local TC track forecasting.

The main approach of the research is focused on finding an atmospheric environment favourable for TC survival (genesis) with the help of commonly accepted knowledge in atmospheric physics that reveals mechanism driving evolution and change of synoptic patterns in the atmosphere, using routinely available observational data, i.e. identification of TCF/TCR areas. The techniques developed are then applied to ensemble the TC track guidances available operationally to formulate an official TC track forecasting.

The results show that TC movement is very dependent on the atmospheric environment surrounding a TC. Whether the environment is favourable (TCF) or resistant (TCR) to survival of a TC system is a vital factor to determine where the TC moving. A systematic approach to the identification of the TCR/TCF areas is a key technique to ensemble available TC track guidances to formulate an official TC track forecasting.

In operational TC forecasting, TC track forecasting is the most important and difficult issue. The results indicate that the systematic approach to TC track forecasting has philosophical justification, solid scientific ground, sound logic and practical viability, and thus, make TC track forecasting easy and effective.

The purpose of this paper is to develop a simplified optimization calculation method to assess cable force of self-anchored suspension bridge based on optimization theories.

A simplified analysis method construction using Matlab is developed, which is then compared with the optimization method that considers the main cable’s geometric nonlinearity with software ANSYS in an actual bridge calculation.

This contrast proves the weak coherence and the adjacently interaction theory unreasonable and its limitation.

This paper analyzes the calculation method to assess cable force of a self-anchored suspension bridge and its application effect.

Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.