A new space-time correlation coefficient and its comparison with Moran's Index on evaluation

Purpose - This article aims to discuss the binary matrix of spatial association which is suggested by Moran, and proposes a new method of the definition of the w matrix to obtain a new space-time correlation coefficient considering the correlation of both time and space. Design/methodology/approach - From the perspective of the multi-dimension of space and time, this article proposes a new computational method of a correlation coefficient considering both temporal and spatial factors, based on the analysis of the characteristics of Moran's Global Index and Moran's Local Index. The number of patents granted in mainland China's provinces and municipalities is taken as an example of multi-dimensional analysis. Findings - The results of quantitative analysis using this space-time correlation coefficient show that the outcomes calculated by this new correlation coefficient are not only highly correlated with Moran's Index, but also have advantages in analyzing the trends of both spatial and temporal indicators simultaneously, which is verified by the illustration of the algorithm. Research limitations/implications - Due to a scarcity of data in China, the algorithm is based on data for the last 20 years, which may not be long enough for this research. Although this does not reduce the value of the conclusions of this article, a closer look should be taken at the effectiveness of the new space-time correlation coefficient in the future. Practical implications - The results of space-time correlation coefficient are highly correlated with Moran's Index. In addition, it can not only analyze the "flow" indicators in a certain period but also analyze the "stock" indicators to reflect both space and time changes. These may reflect superiority of space-time correlation coefficient to Moran's Index. Originality/value - This new correlation coefficient that considers both temporal and spatial factors and will provide a more scientific and effective tool for spatial econometric analysis in time and space changes of management on society and the economy.