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The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can measure the dynamic periodic fluctuation rules of the objects, and most of these models do not have affinities, which results in instabilities of the relational results because of sequence translation. The paper aims to discuss these issues.

Fourier transform functions are used to fit the system behaviour curves, redefine the area difference between the curves and construct a grey relational model based on discrete Fourier transform (DFTGRA).

To verify its validity, feasibility and superiority, DFTGRA is applied to research on the correlation between macroeconomic growth and marine economic growth in China coastal areas. It is proved that DFTGRA has the superior properties of affinity, symmetry, uniqueness, etc., and wide applicability.

DFTGRA can not only be applied to equidistant and equal time sequences but also be adopted for non-equidistant and unequal time sequences. DFTGRA can measure both the global relational degree and the dynamic correlation of the variable cyclical fluctuation between sequences.

The purpose of this paper is to review the four large and two small fluctuations in China’s economic growth since the reform and opening up, which can be further divided into five periods of economic upturn and six periods of economic downturn.

This paper also analyzes the performance, causes and practical countermeasures of these fluctuations and summarizes the experience and lessons from the eight aspects of dealing with economic downturn and stabilizing growth since the reform and opening up.

At last, the paper puts forward some measures to cope with economic downturn and stabilize growth under the new normal in the new era.

Any country’s economic growth is a tortuous process with many fluctuations. The rate of economic growth cannot rise or go down straight for a long time, and China’s economic growth is no exception. The drastic fluctuations of economic growth can lead to serious overproduction, waste of resources, increased unemployment, decreased income or supply shortages, rising prices and decline of living standards.

Using Social Network Analysis (SNA), this paper examines the inter-provincial logistics relationships in China. Based on the annual data of inter-provincial railway logistics quantity during the period 1998-2009, the degree of interconnection between regions could imply intensified trends of regional economic integration.

The main results of the logistic relationships in China are as follows: the regional logistic interconnection, especially between western and eastern China has increased continuously, which would imply a rising national economic integration. However, the increased centralization index and the average Degree Centrality level imply that a logistics bottleneck has intensified in several hub provinces.

Secondly, logistic center provinces evaluated by the Degree Centrality have changed. In 2009, Hebei, Liaoning, Jiangsu, Shandong, Henan and Sichuan provinces revealed the highest inward Degree Centrality. Sichuan Province is the region that most surprisingly increased its centrality.

Thirdly, the number of logistic hub provinces, evaluated by the Degree Betweenness Centrality, has increased. In 2008, Henan province was only a focal hub but in 2009, Shandong, Hubei, Sichuan provinces became logistic hubs.

Lastly, the Community Modularity which analyzed grouping structures shows that there are three time-consistent communities. This means that even though there is enhanced between-region integration, the inter-regional inter-connection is more important in explaining the regional logistic relationship.

This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model. This behavior will be compared with a measure of online presence, search engine results as measured by Google Trends.

The study sample is comprised by the companies listed at the STOXX® Global 3000 Travel and Leisure. Google Finance and Yahoo Finance, along with Google Trends, were used, respectively, to obtain the data of stock prices and search results, for a period of five years (October 2012 to October 2017). To guarantee certain comparability between the two data sets, weekly observations were collected, with a total figure of 118 firms, two time series each (price and search results), around 61,000 observations.

Relationships between the two data sets are explored, with theoretical implications for the fields of economics, finance and management. Tourist corporations were analyzed owing to their growing economic impact. The estimations are initially consistent with long memory; so, they suggest that both stock market prices and online search trends deserve further exploration for modeling and forecasting. Significant differences owing to country and sector effects are also shown.

This research contributes in two different ways: it demonstrate the potential of a new tool for the analysis of relevant time series to monitor the behavior of firms and markets, and it suggests several theoretical pathways for further research in the specific topics of asymmetry of information and corporate transparency, proposing pertinent bridges between the two fields.

The purpose of this article is to promote an innovative approach to education development projects by the application of business modelling tools and methods.

The proposed method is based on tools and methods from the business modelling area, such as stakeholder mapping, SWOT analysis, business modelling canvas and scenario analysis. The applicability of the approach is illustrated by a case study conducted on an engineering programme, where qualitative and quantitative data were gathered through interviews, surveys and workshops.

Utilising business modelling tools for development projects in higher education gives several benefits: (1) knowledge-informed decision making; the methods require good understanding of the current situation as well as possible strategies to be applied, that is data gathering is necessary before decision making; (2) structured decision making by applying a step-by-step approach for the development project; (3) including different stakeholder's perspectives in order to gain a holistic understanding and avoid sub optimisation.

The approach promotes innovation and action driven development rather than a bureaucratic and metric based improvement process. Tools and models from the business area have previously been applied for educational development. However, a holistic business modelling approach for educational development has not yet been applied.