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Article

Jie Jian, Milin Wang, Lvcheng Li, Jiafu Su and Tianxiang Huang

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is…

Abstract

Purpose

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is to propose an integrated multi-criteria approach and a decision optimization model of partner selection for CPI from the perspective of knowledge collaboration.

Design/methodology/approach

First, the criteria for partner selection are presented, considering comprehensively the knowledge matching degree of the candidates, the knowledge collaborative performance among the candidates, and the overall expected revenue of the CPI alliance. Then, a quantitative method based on the vector space model and the synergetic matrix method is proposed to obtain a comprehensive performance of candidates. Furthermore, a multi-objective optimization model is developed to select desirable partners. Considering the model is a NP-hard problem, a non-dominated sorting genetic algorithm II is developed to solve the multi-objective optimization model of partner selection.

Findings

A real case is analyzed to verify the feasibility and validity of the proposed model. The findings show that the proposed model can efficiently select excellent partners with the desired comprehensive attributes for the formation of a CPI alliance.

Originality/value

Theoretically, a novel method and approach to partner selection for CPI alliances from a knowledge collaboration perspective is proposed in this study. In practice, this paper also provides companies with a decision support and reference for partner selection in CPI alliances establishment.

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Article

Tianxiang Li, Wusheng Yu, Tomas Baležentis, Jing Zhu and Yueqing Ji

The purpose of this paper is to identify the effects of recent demographic transition and rising labor costs on agricultural production structure and pattern in China…

Abstract

Purpose

The purpose of this paper is to identify the effects of recent demographic transition and rising labor costs on agricultural production structure and pattern in China during 1998-2012.

Design/methodology/approach

The authors, first, theoretically discuss the effects of changing relative input prices due to rising labor cost on producers’ decisions regarding input mix (substitution effect), output level, and product quality (output effect). A logarithmic mean Divisia index decomposition method is then applied to empirically identify these effects at aggregated levels, followed by an analysis based on the visualization of land use indicators on changing cropping patterns across Chinese provinces.

Findings

The authors find that tightened effective agricultural labor supply and rises in rural labor costs are associated with divergent changes in input mixes and output choices across products. Producers of land-intensive products focusing more on input mix adjustment, while those of labor-intensive products seem to more likely to adjust output choices. Producers’ adaption strategies also varied across Chinese provinces due to natural conditions, leading to shifts and concentrations in the regional distribution of agricultural products, with lower-value bulk products concentrating in the plain areas, whereas higher-value horticulture products increasingly prevailing in sloped areas.

Originality/value

This paper illustrates how adjustments in input mixes and output choice in Chinese agriculture counteracted disadvantages caused by rising labor costs and how such adjustments are product and region specific. Based on these observations, implications regarding further innovations in production technology and institutional arrangements needed within China’s agricultural sector are highlighted in the paper.

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Article

Tianxiang Yao and Zihan Wang

According to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition…

Abstract

Purpose

According to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.

Design/methodology/approach

First, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.

Findings

The model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.

Originality/value

This paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.

Details

Grey Systems: Theory and Application, vol. 11 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

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Article

Hong Gao, Tianxiang Yao and Xiaoru Kang

The purpose of this paper is to predict the population of Anhui province. The authors analyze the trend of the main demographic indicators.

Abstract

Purpose

The purpose of this paper is to predict the population of Anhui province. The authors analyze the trend of the main demographic indicators.

Design/methodology/approach

On the basis of the main methods of statistics, this paper studies the tendency of the population of Anhui province. It mainly analyzes the sex structure and the age structure of the current population. Based on the GM(1,1) model, this paper forecasts the total population, the population sex structure, and the population age structure of Anhui province in the next ten years.

Findings

The results show that the total population was controlled well, but there have been many problems of the population structure, such as the aging population, high sex ratio, heavy social dependency burden, and the declining labor force.

Social implications

This paper forecasts the main indexes of the population of Anhui province and provides policy recommendations for the government and the relevant departments.

Originality/value

This paper utilizes data analysis method and the grey forecasting model to study the tendency of the population problems in Anhui province.

Details

Grey Systems: Theory and Application, vol. 7 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

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Article

Sifeng Liu, Bo Zeng, Jiefang Liu, Naiming Xie and Yingjie Yang

– The purpose of this paper is to provide a foundational reference and practical guidance for modelling small and poor data with incomplete information.

Abstract

Purpose

The purpose of this paper is to provide a foundational reference and practical guidance for modelling small and poor data with incomplete information.

Design/methodology/approach

The definitions of four basic models of GM(1, 1), such as Even Grey Model (EGM), Original Difference Grey Model (ODGM), Even Difference Grey Model (EDGM) and Discrete Grey Model (DGM), are put forward. The properties and characteristics of different models are studied and their equivalence are proved. The suitable sequences of different models are studied by simulation and analysis with homogeneous exponential sequences, nonhomogeneous exponential increasing sequences and vibration sequences.

Findings

The main conclusions have been obtained as follows: first, the three discrete models of ODGM, EDGM and DGM are suitable for homogeneous exponential sequences or sequences which close to a homogeneous exponential sequence; and second the EGM are suitable for nonhomogeneous exponential increasing sequences and vibration sequences.

Practical implications

The outcome obtained in this paper can be consulted for model selection in the course of practical modelling.

Originality/value

This paper systematically defined the four basic forms of model GM(1, 1) and studied their properties and characteristics, especially their suitable sequences. Although significant progress has been made in this field, such a systematic study on these models and their suitable sequences is still missing as far as we know. It can provide reference and basis for people to choose the correct model in the actual modelling process.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Content available
Article

Abstract

Details

Grey Systems: Theory and Application, vol. 2 no. 2
Type: Research Article
ISSN: 2043-9377

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