Search results
1 – 2 of 2More and more statistics have repeatedly shown that as the economic development has entered the New Normal, the Chinese fiscal system has experienced tremendous changes. Although…
Abstract
Purpose
More and more statistics have repeatedly shown that as the economic development has entered the New Normal, the Chinese fiscal system has experienced tremendous changes. Although chance cannot be ruled out, much of those changes indicate trends, and they can even be said to be the result of the law of economic development. These trends and changes have repeatedly demonstrated that, as a reflection and an inevitable result of the economic developing speed shift, structural adjustment and energy conversion, the Chinese fiscal system, far from the conventional operating state, has progressed on a new path. The paper aims to discuss this issue.
Design/methodology/approach
This paper systematically analyzes several new trends and changes in the Chinese fiscal system under the New Normal. First, revenue growth has experienced a sharp downward trend, while the tax elasticity coefficient has declined rapidly. Second, fiscal expenditure has risen against the tendency, while the rigidity of expenditure has kept on increasing.
Findings
Considering the present fiscal and taxation system reform with the analysis above, it can be seen that if the reform’s progress for the past two years is slower than expected – thus, preventing the effects of all aspects from a timely achievement – then, in the recent period, the agreement on the fiscal and taxation system reform will be reached and challenges entirely different from the past, including sharp slowdown in revenue growth rate, fiscal expenditure rising against trend and increases in fiscal deficit and government debts will be faced. The factors encouraging the reform are gathering gradually. The growth of the strength to push the reform forward is speeding up. And the pace of the reform in relevant areas is quickening.
Originality/value
In the face of those trends and changes, on the one hand, the authors should deeply understand and accurately grasp them through a comprehensive summary and systematic analysis. On the other hand, a series of conventional ideas, thoughts and strategies should be adjusted comprehensively and duly. Taking a train of new ideas, thoughts and strategies, the authors ought to actively adapt to and initiate a new Chinese fiscal structure under the New Normal of China’s economy.
Details
Keywords
Ke Zhang and Ailing Huang
The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user…
Abstract
Purpose
The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.
Design/methodology/approach
To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.
Findings
In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.
Originality/value
This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.
Details