Yali Han, Krishna P. Paudel, Junyi Wan and Qinying He
China's economy has transformed from a high-speed growth phase to a high-quality development phase. The agriculture sector has grown substantially since the economic reform in…
Abstract
Purpose
China's economy has transformed from a high-speed growth phase to a high-quality development phase. The agriculture sector has grown substantially since the economic reform in 1978. Considering the five-year plan (FYP) as a collection of policies, this study explores the relationship between the FYP and agricultural total factor productivity (TFP).
Design/methodology/approach
This study uses 31 provincial-level panel data of the five FYPs from 1996 to 2020. The data envelopment analysis (DEA) is used to compute Malmquist productivity indexes. The authors analyze the temporal and spatial changes and convergences of China's agricultural TFP, and investigate the impact of economic planning on China's agricultural TFP and its regional difference.
Findings
There is a slow but upward growth trend in China's agricultural TFP. The technical change has played a leading role in the growth of China's agricultural TFP. The agricultural TFP of all provinces has shown a “catch-up” effect and is developing toward their respective steady-state levels. The regional difference in productivity growth among the eastern, central and western regions exists. Test results show that the FYP has a positive effect on the agricultural TFP, and the effect has obvious regional heterogeneity. The FYP also plays a positive role in the gross value of agricultural output, and the impact effect is greater than that on the improvement of agricultural productivity.
Originality/value
There are many forms of industrial policy in China, among which the FYP is the guiding document of industrial policy, which makes a systematic plan for industrial development in the subsequent five years. The development objectives, guidelines and overall deployment for agriculture in the FYP not only describe the general context of China's agricultural development but also show the key ideas of agricultural development. Therefore, this study explores its impact on agricultural quality development from the perspective of FYP. The results provide evidence for examining the governance performance of the government and the objective evaluation and restraint of the FYP. As agriculture moves toward the stage of high-quality development, the Chinese government should strengthen the critical guiding role of the FYP and pay attention to quality indicators such as technical progress, efficiency improvement and regional coordination in the formulation of the FYP.
Details
Keywords
Yiqiang Wang, Yazhou Jia, Junyi Yu and Shangfeng Yi
To assess and improve the reliability of computerized numerical control (CNC) lathes, it is essential to collect field failure information throughout the products’ life and…
Abstract
To assess and improve the reliability of computerized numerical control (CNC) lathes, it is essential to collect field failure information throughout the products’ life and perform analysis on these data. This paper describes the collection of field failure data, codification of data and establishment of the field failure database for CNC lathes and gives some examples of the kind of analysis possible when sufficient data have been collected and the database has been accrued.
Details
Keywords
Yiping Jiang, Shanshan Zhou, Jie Chu, Xiaoling Fu and Junyi Lin
This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock…
Abstract
Purpose
This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?
Design/methodology/approach
This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.
Findings
The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.
Originality/value
This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.
Details
Keywords
Yui-yip Lau, Lok Ming Eric Cheung, Eve Man Hin Chan and Stephanie Wing Lee
The present study adopts the analytical framework of new managerialism (NM) to explore the progress, challenges and outlook of self-financing post-secondary institutions in Hong…
Abstract
Purpose
The present study adopts the analytical framework of new managerialism (NM) to explore the progress, challenges and outlook of self-financing post-secondary institutions in Hong Kong since 2000. This study also identified issues and related managerial implications for developing this niche form of higher education in Hong Kong.
Design/methodology/approach
This study conducted a critical review of self-financing post-secondary institutions in Hong Kong, including the sub-degree and degree sectors, via collecting a series of policy documents and archives from the Legislative Council of Hong Kong, the Public Records Office and other government bodies. To supplement the findings, semi-structured in-depth interviews of 18 academic staff of Hong Kong's self-financing post-secondary institutions were carried out.
Findings
The study shows that self-financing post-secondary institutions not only encounter challenges related to insufficient resources but also face pressure from accreditation requirements of various international organisations. The study also suggests that massification and privatisation of self-financing post-secondary institutions, and embracing a managerial approach for operation and governance will induce a new wave of self-financing post-secondary institutions in the near future.
Originality/value
This study offers insights for self-financing post-secondary institutions into implementing appropriate strategies to maintain competitiveness and retain talents in the coming years.
Details
Keywords
Hao Zhang, Weilong Ding, Qi Yu and Zijian Liu
The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing…
Abstract
Purpose
The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing data, ensuring reliable analysis outcomes.
Design/methodology/approach
The Conv-DMSA model employs a combination of self-attention mechanisms and convolutional networks to handle the complexities of multivariate time series data. The convolutional network is adept at learning features across uneven time intervals through an imputation feature map, while the Diagonal Mask Self-Attention (DMSA) block is specifically designed to capture time dependencies and feature correlations. This dual approach allows the model to effectively address the temporal imbalance, feature correlation and time dependency challenges that are often overlooked in traditional imputation models.
Findings
Extensive experiments conducted on two public data sets and a real project data set have demonstrated the adaptability and effectiveness of the Conv-DMSA model for imputing missing data. The model outperforms baseline methods by significantly reducing the Root Mean Square Error (RMSE) metric, showcasing its superior performance. Specifically, Conv-DMSA has been found to reduce RMSE by 37.2% to 63.87% compared to other models, indicating its enhanced accuracy and efficiency in handling missing data in multivariate time series.
Originality/value
The Conv-DMSA model introduces a unique combination of convolutional networks and self-attention mechanisms to the field of missing data imputation. Its innovative use of a diagonal mask within the self-attention block allows for a more nuanced understanding of the data’s temporal and relational aspects. This novel approach not only addresses the existing shortcomings of conventional imputation methods but also sets a new standard for handling missing data in complex, multivariate time series data sets. The model’s superior performance and its capacity to adapt to varying levels of missing data make it a significant contribution to the field.