Comparative Analysis of Rural Consumption Expenditure in China

The disparity of consumption expenditure among rural areas in China was studied. Then income and living expenditure of rural residents were divided into 5 grades. Principle and method of Cluster Analysis were introduced. Next, Cluster Analysis was adopted to research the disparity of rural consumption expenditure among various areas. Results showed that income and consumption expenditure of 31 districts, cities and provinces could be divided into 5 classes. Shanghai City was the only city rated as the first-class areas with highest income and consumption. 7 cities and provinces were rated as the top three classes of areas. Taking Hebei and Jilin Province as the representatives, most parts of the fourth-class areas were located in northeast part of China with poor cultivated land, which will lead to slow development of rural economy. The fifth-class areas represented by Chongqing City and Sichuan Province were constrained by natural factors with frequent disasters as well as underdevelopment of industry and agriculture, which could not play an improving role in rural development. On this basis, relevant policy countermeasures were put forward

Trust and contracts: empirical evidence

Trust between parties should drive contract design: if parties were suspicious about each others’ reaction to unplanned events, they might agree to pay higher costs of negotiation ex ante to complete contracts. Using a unique sample of U.S. consulting contracts and a negative shock to trust between shareholders/managers (principals) and consultants (agents) staggered across space and over time, we find that lower trust increases contract completeness. Not only the complexity but also the verifiable states of the world covered by contracts increase after trust drops. The results hold for several novel text-analysis-based measures of contract completeness and do not arise in falsification tests. At the clause level, we find that non-compete agreements, confidentiality, indemnification, and termination rules are the most likely clauses added to contracts after a negative shock to trust and these additions are not driven by new boilerplate contract templates. These clauses are those whose presence should be sensitive to the mutual trust between principals and agents

Trust and Contracts: Empirical Evidence

Trust between parties should drive the negotiation and design of contract: if parties did not trust each others' reaction to unplanned events, they might agree to pay higher costs of negotiation to complete contracts. Using a unique sample of U.S. principal-agent consulting contracts and a negative shock to trust between parties staggered across space and over time, we find that lower trust increases contract completeness. Not only contract complexity but also the verifiable states of the world contracts cover increase after a drop in trust. The results hold for several text-analysis-based measures of completeness and do not arise when agents are also principals (shareholders) or in other falsification tests. Non-compete agreements, confidentiality and indemnification clauses, and restrictions to agents' actions are more likely to be added to contracts signed in the same locations, same industries, and same years after a negative shock to trust

Predicting sales and cross-border e-commerce supply chain management using artificial neural networks and the Capuchin search algorithm

Abstract E-commerce provides a large selection of goods for sale and purchase, which promotes regular transactions and commodity flows. Efficient distribution of goods and precise estimation of customer wants are essential for cost reduction. In order to improve supply chain efficiency in the context of cross-border e-commerce, this article combines machine learning approaches with the Internet of Things. The suggested approach consists of two main stages. Order prediction is done in the first step to determine how many orders each merchant is expected to get in the future. In the second phase, allocation operations are conducted and resources required for each retailer are supplied depending on their needs and inventory, taking into account each store’s inventory as well as the anticipated sales level. This suggested approach makes use of a weighted mixture of neural networks to anticipate sales orders. The Capuchin Search Algorithm (CapSA) is used in this weighted combination to concurrently enhance the learning and ensemble performance of models. This indicates that an effort is made to reduce the local error of the learning model at the model level via model weight adjustments and neural network configuration. To guarantee more accurate output from the ensemble model, the best weight for each individual component is found at the ensemble model level using the CapSA method. This method yields the ensemble model’s final output in the form of weighted averages by choosing suitable weight values. With a Root Mean Squared Error of 2.27, the suggested technique has successfully predicted sales based on the acquired findings, showing a minimum decrease of 2.4 in comparison to the comparing methodologies. Additionally, the suggested method’s strong performance is shown by the fact that it was able to minimize the Mean Absolute Percentage Error by 14.67 when compared to other comparison approaches

Numerical Simulation of One-Dimensional Fractional Nonsteady Heat Transfer Model Based on the Second Kind Chebyshev Wavelet

In the current study, a numerical technique for solving one-dimensional fractional nonsteady heat transfer model is presented. We construct the second kind Chebyshev wavelet and then derive the operational matrix of fractional-order integration. The operational matrix of fractional-order integration is utilized to reduce the original problem to a system of linear algebraic equations, and then the numerical solutions obtained by our method are compared with those obtained by CAS wavelet method. Lastly, illustrated examples are included to demonstrate the validity and applicability of the technique

Numerical Simulation of Fractional Control System Using Chebyshev Polynomials

In the current study, a numerical scheme based on Chebyshev polynomials is proposed to solve the problem of fractional control system. The operational matrix of fractional derivative is derived and that is used to transform the original problem into a system of linear equations. Lastly, several numerical examples are presented to verify the effectiveness and feasibility of the given method

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight) motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration) control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square) error is 1.253 mrad when tracking 10° 0.2 Hz signal

Comparative Analysis of Rural Consumption Expenditure in China

The disparity of consumption expenditure among rural areas in China was studied. Then income and living expenditure of rural residents were divided into 5 grades. Principle and method of Cluster Analysis were introduced. Next, Cluster Analysis was adopted to research the disparity of rural consumption expenditure among various areas. Results showed that income and consumption expenditure of 31 districts, cities and provinces could be divided into 5 classes. Shanghai City was the only city rated as the first-class areas with highest income and consumption. 7 cities and provinces were rated as the top three classes of areas. Taking Hebei and Jilin Province as the representatives, most parts of the fourth-class areas were located in northeast part of China with poor cultivated land, which will lead to slow development of rural economy. The fifth-class areas represented by Chongqing City and Sichuan Province were constrained by natural factors with frequent disasters as well as underdevelopment of industry and agriculture, which could not play an improving role in rural development. On this basis, relevant policy countermeasures were put forward.Consumption expenditure, Engel coefficient, Cluster Analysis, China, Community/Rural/Urban Development, Financial Economics, Research Methods/ Statistical Methods,