PurposeThis paper aims to explore the factors that affect housing prices as per Chinese articles indexed in the Chinese Science Citation Database (CSCD). There were different foci regarding what drove housing prices in China in Chinese articles, and international journal articles in English. As most previous English articles only threw light on international research, it motivated the researchers to systematically review Chinese literature’s factors that affected housing prices in China.Design/methodology/approachThis paper reviewed housing price research articles indexed in the two largest Chinese academic research databases: the CSCD and China Knowledge Infrastructure Engineering Database (CNKI.NET). It systematically collected the data and adopted descriptive analysis techniques and synthesis.FindingsThis research reviewed the literature published from 2015 to 2020 and revealed some unique factors affecting China's housing prices. For example, research focused on administrative aspects such as macroeconomic regulation and control (often known as macro control). Authors of Chinese articles suggested that the two-child policy affected housing prices, which differed from that in the English journal articles. The research results implied that researchers should read top Chinese journals on top of good international journals when they study China's real estate market in the future.Research limitations/implicationsBecause the domestic real estate market started late, domestic real estate transaction data and real estate-related statistics are more difficult to obtain. The research is mostly based on the relationship between supply and demand, government policy and individual consumer factors, and the sample has a short time span.Practical implicationsAs China is a planned economy country, administrative factors are one main factor that affects the housing price. There were a significant number of articles in Chinese that considered this factor to be the main driver of the real estate price. It included government investment and macro-control, i.e. direct government intervention to cool down the overheated economy. Yet, there are few English articles that threw light on this factor including the commodity housing supply and government behaviour that affect housing price. The second-child policy, which is unique in China, also played an important role in the determination of the housing price. In the articles indexed in CNKI, the second-child rate, willingness to have a second child or having a second child were mentioned in the Chinese articles but not the English ones.Social implicationsIn this paper, the economic, social, administrative and environmental factors were summarised, which basically covered all the factors affecting housing prices. The administrative factors were a special group of factors that affect the housing price because of the country's planned economic system. Secondly, it provided useful information to real estate development enterprises in China. To make a correct investment and management decision, real estate development enterprises must understand the actual situation and possible problems of the industry. In this study, we analysed the research literature on the real estate industry in China for the period from 2015 to 2020 one by one and determined the influencing factors of the housing price, which provided references for effective cost control. Thirdly, it allows the public to understand and grasp the real estate industry. As the housing price has been continuously increasing, the public pays increasing attention to the real estate industry. Through the literature analysis of the impact of real estate prices, this paper revealed the elements of house price expenses, which makes it convenient for ordinary people to understand the real estate industry.Originality/valueThis study allows foreigners who do not know Chinese to know more about factors that drove housing prices from the Chinese perspective. It also provides insights to overseas developers who wish to enter the property market in China. The results can be generalised to other non-English-speaking real estate research.
PurposeThe purpose of this paper is to explore the internal interaction mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth from a systematic perspective, based on which this work forecasts their future development trends.Design/methodology/approachIn this study, a multivariate grey model is applied to the prediction of marine scientific research and education, industrial structure upgrading and marine economic growth. Considering the impact of the COVID-19 on marine development, this paper introduces the weakening buffer operator into MGM(1,m) and constructs the AWBO-MGM(1,m) model. To verify the validity and accuracy of the new model, this paper uses AWBO-MGM(1,m), MGM(1,m), GM(1,N), GM(1,1), back propagation neural network and linear regression models for simulation and prediction based on the data from 2010 to 2021, respectively.FindingsFrom the theoretical perspective, the development of marine scientific research and education can accelerate industrial upgrading and promote marine economic growth by providing high-quality talents, promoting marine science and technology progress and reducing transaction costs; while the upgrading of marine industrial structure and marine economic growth can promote the development of marine scientific research and education by guiding social capital, enhancing talent demand and stimulating market vitality. From the empirical analysis, the AWBO-MGM(1,m) model can effectively deal with epidemic shocks and has higher fitting and prediction accuracy than the other five comparative models.Practical implicationsThe government should pay attention to the construction of marine scientific research and education, so as to provide high-quality talents and advanced scientific research results for the high-quality development of marine economy. On the basis of using science and technology to firmly build the primary and secondary marine industries, the government should actively guide the labor, capital and other factors of production to the tertiary industry, thereby promoting the optimization and upgrading of marine industrial structure.Originality/valueOn the one hand, the interplay mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth is analyzed from a systematic perspective; on the other hand, the enhanced AWBO-MGM(1,m) possesses higher forecasting performance and is applicable to the systemic multivariate forecasting problem in the presence of outstanding external shocks.
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