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Article
Publication date: 17 April 2023

Ping Li, Zhipeng Chang and Wenhe Chen

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making…

111

Abstract

Purpose

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

Design/methodology/approach

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

Findings

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

Originality/value

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

Details

Kybernetes, vol. 53 no. 9
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 8 January 2025

Zhenkuo Ding, Zhipeng Chen and Sheng Huang

This paper aims to examine the impact of top executives’ military experience on the internationalisation process of firms, as well as the boundary conditions of this impact.

32

Abstract

Purpose

This paper aims to examine the impact of top executives’ military experience on the internationalisation process of firms, as well as the boundary conditions of this impact.

Design/methodology/approach

The hypotheses are tested using 8,759 imbalanced panel samples in 1,718 China’s A-share listed firms.

Findings

The findings show that the military experience of top executives has a positive impact on the internationalisation process (scope, speed and rhythm) of firms. The managerial discretion strengthens the influence of top executives’ military experience on the internationalisation scope and speed but weakens its influence on the internationalisation rhythm.

Originality/value

The study contributes to the literature by testing the relationships that among military experience of top executives, firm internationalisation process and managerial discretion. The authors also help practitioners to become aware of the importance that the military experience of top executives have on firm internationalisation process, and managerial discretion can exert contingent influence on this relationship.

Details

Multinational Business Review, vol. 33 no. 1
Type: Research Article
ISSN: 1525-383X

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Article
Publication date: 29 November 2024

Yi Huang, Zhipeng Huang, Gang Xu and Yan Zhang

Grassland degradation is a global ecological issue that inevitably leads to low livestock production efficiency (LPE). Adoption of appropriate technology is an effective way to…

79

Abstract

Purpose

Grassland degradation is a global ecological issue that inevitably leads to low livestock production efficiency (LPE). Adoption of appropriate technology is an effective way to improve productivity. However, the rate of technology adoption among herders in less developed pastoral areas is low. Therefore, it is critical to improve the level of technology adoption in order to increase LPE.

Design/methodology/approach

Based on remote sensing data and survey datasets of herder households in China’s Qinghai–Xizang Plateau, this paper innovatively constructs a stochastic production frontier model incorporating grassland productivity (i.e. grassland total net primary productivity) to accurately evaluate LPE and uses fractional regression models to determine the impact of technology adoption on LPE.

Findings

The results show that grassland productivity is essential to estimating LPE, and failing to account for it will result in overestimation. Technology adopters have a technical advantage with respect to average LPE (0.596) when compared with non-adopters (0.540), and technology adoption positively contributes to LPE. Furthermore, compared with profit-seeking technology, pro-environmental technology contributes more to improving LPE, and the combined adoption of both technologies leads to a markedly greater enhancement in LPE.

Originality/value

Few studies have empirically analyzed the economic benefits of technologies that most smallholders can afford, and few measure LPE considering grassland productivity. This study fills these gaps, and the findings are highly relevant for policies aimed at encouraging technology adoption and facilitating more efficient livestock production.

Details

China Agricultural Economic Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-137X

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Article
Publication date: 24 September 2024

Zhipeng Liang, Chunju Zhao, Huawei Zhou, Yihong Zhou, Quan Liu, Tao Fang and Fang Wang

The spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a…

39

Abstract

Purpose

The spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a continuous high-strength and high-density construction process. Furthermore, the complicated construction technology and limited space resources aggravate the spatial–temporal conflicts in the process of space resource allocation and utilization, directly affecting the pouring quality and progress of concrete. To promote the high-strength, quality-preserving and rapid construction of dams and to clarify the explosion moment and influence degree of the spatial–temporal conflicts of construction machinery during the pouring process, a quantification method and algorithm for a “Conflict Bubble” (CB) between construction machines is proposed based on the “Time–Space Microelement” (TSM).

Design/methodology/approach

First, the concept of a CB is proposed, which is defined as the spatial overlap of different entities in the movement process. The subsidiary space of the entity is divided into three layered spaces: the physical space, safe space and efficiency space from the inside to the outside. Second, the processes of “creation,” “transition” and “disappearance” of the CB at different levels with the movement of the entity are defined as the evolution of the spatial–temporal state of the entity. The mapping relationship between the spatial variation and the running time of the layered space during the movement process is defined as “Time–Space” (TS), which is intended to be processed by a microelement.

Findings

The quantification method and algorithm of the CB between construction machinery are proposed based on the TSM, which realizes the quantification of the physical collision accident rate, security risk rate and efficiency loss rate of the construction machinery at any time point or time period. The risk rate of spatial–temporal conflicts in the construction process was calculated, and the outbreak condition of spatial–temporal conflict in the pouring process was simulated and rehearsed. The quantitative calculation results show that the physical collision accident rate, security risk rate and efficiency loss rate of construction machinery at any time point or time period can be quantified.

Originality/value

This study provides theoretical support for the quantitative evaluation and analysis of the spatial–temporal conflict risk in the pouring construction process. It also serves as a reference for the rational organization and scientific decision-making for pouring blocks and provides new ideas and methods for the safe and efficient construction and the scientific and refined management of dams.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 18 October 2024

Xinyu Mei, Feng Xu, Zhipeng Zhang and Yu Tao

Workers' unsafe behavior is the main cause of construction safety accidents, thereby highlighting the critical importance of behavior-based management. To compensate for the…

173

Abstract

Purpose

Workers' unsafe behavior is the main cause of construction safety accidents, thereby highlighting the critical importance of behavior-based management. To compensate for the limitations of computer vision in tackling knowledge-intensive issues, semantic-based methods have gained increasing attention in the field of construction safety management. Knowledge graph provides an efficient and visualized method for the identification of various unsafe behaviors.

Design/methodology/approach

This study proposes an unsafe behavior identification framework by integrating computer vision and knowledge graph–based reasoning. An enhanced ontology model anchors our framework, with image features from YOLOv5, COCO Panoptic Segmentation and DeepSORT integrated into the graph database, culminating in a structured knowledge graph. An inference module is also developed, enabling automated the extraction of unsafe behavior knowledge through rule-based reasoning.

Findings

A case application is implemented to demonstrate the feasibility and effectiveness of the proposed method. Results show that the method can identify various unsafe behaviors from images of construction sites and provide mitigation recommendations for safety managers by automated reasoning, thus supporting on-site safety management and safety education.

Originality/value

Existing studies focus on spatial relationships, often neglecting the diversified spatiotemporal information in images. Besides, previous research in construction safety only partially automated knowledge graph construction and reasoning processes. In contrast, this study constructs an enhanced knowledge graph integrating static and dynamic data, coupled with an inference module for fully automated knowledge-based unsafe behavior identification. It can help managers grasp the workers’ behavior dynamics and timely implement measures to correct violations.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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