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Article
Publication date: 2 February 2015

Haitao Wu, Shijun Ding and Guanghua Wan

The purpose of this paper is to apply a poverty level decomposition approach to decompose the poverty by income sources and investigate the impact of government transfers…

Abstract

Purpose

The purpose of this paper is to apply a poverty level decomposition approach to decompose the poverty by income sources and investigate the impact of government transfers on income inequality and rural poverty.

Design/methodology/approach

This paper uses the decomposition method of inequality and the decomposition method of poverty level by resource endowments to decompose the overall inequality and the overall poverty by income sources.

Findings

It is found that unequal income distribution rather than income endowments is mainly responsible for the existence of poverty. Government transfers and relief income, aiming at the poor, help alleviate inequality and poverty, but are not targeting the poorest. Unequal distribution of production subsidies actually lead to higher poverty incidence.

Research limitations/implications

This paper has revealed that the poverty issue cannot be resolved with economic development alone if the issues including the inequality in income distribution are not solved. It is important to make government transfers/subsidies pro-poor.

Originality/value

A poverty level decomposition approach is first used to decompose the poverty by income sources in China.

Details

China Agricultural Economic Review, vol. 7 no. 1
Type: Research Article
ISSN: 1756-137X

Keywords

Content available
Article
Publication date: 6 March 2017

Jiaqi Lu, Shijun Liu, Lizhen Cui, Li Pan and Lei Wu

A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the…

Abstract

Purpose

A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Design/methodology/approach

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

Findings

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Originality/value

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

Details

International Journal of Crowd Science, vol. 1 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Content available
Article
Publication date: 9 December 2019

Xudong Lu, Shipeng Wang, Fengjian Kang, Shijun Liu, Hui Li, Xiangzhen Xu and Lizhen Cui

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of…

Abstract

Purpose

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

Design/methodology/approach

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

Findings

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

Originality/value

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

Details

International Journal of Crowd Science, vol. 3 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

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Article
Publication date: 6 May 2020

Saeed Akbari, Farzad Pour Rahimian, Moslem Sheikhkhoshkar, Saeed Banihashemi and Mostafa Khanzadi

Successful implementation of infrastructure projects has been a controversial issue in recent years, particularly in developing countries. This study aims to propose a…

Abstract

Purpose

Successful implementation of infrastructure projects has been a controversial issue in recent years, particularly in developing countries. This study aims to propose a decision support system (DSS) for the evaluation and prediction of project success while considering sustainability criteria.

Design/methodology/approach

To predict sustainable success factor, the study first developed its sustainable success factors and sustainable success criteria. These then formed a decision table. A rough set theory (RST) was then implemented for rules generation. The decision table was used as the input for the rough set, which returned a set of rules as the output. The generated rulesets were then filtered in fuzzy inference system (FIS), before serving as the basis for the DSS. The developed prediction tool was tested and validated by applying data from a real infrastructure project.

Findings

The results show that the developed rough set fuzzy method has strong ability in evaluation and prediction of the project success. Hence, the efficacy of the DSS is greatly related to the rule-based system, which applies RST to generate the rules and the result of the FIS was found to be valid via running a case study.

Originality/value

Use of DSS for predicting the sustainable success of the construction projects is gaining progressive interest. Integration of RST and FIS has also been advocated by the seminal literature in terms of developing robust rulesets for impeccable prediction. However, there is no preceding study adopting this integration for predicting project success from the sustainability perspective. The developed system in this study can serve as a tool to assist the decision-makers to dynamically evaluate and predict the success of their own projects based on different sustainability criteria throughout the project life cycle.

Details

Construction Innovation , vol. 20 no. 4
Type: Research Article
ISSN: 1471-4175

Keywords

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