In the era of green logistics,digital transformation has become an effective means for the logistics industry’s high-quality development.Using listed companies in China’s logistics industry from 2010 to 2021 as the ...In the era of green logistics,digital transformation has become an effective means for the logistics industry’s high-quality development.Using listed companies in China’s logistics industry from 2010 to 2021 as the research samples,this paper conducts an empirical test on the impact of the digital transformation of logistics enterprises on their green in-novation.Specifically,enterprise digital transformation indicators are constructed through the text analysis method,and the fixed-effects model is applied for analysis.The results indicate that the digital transformation of logistics enterprises has a significant promoting effect on their green innovation;the promoting effect of the digital transformation of logistics enterprises on green innovation is primarily achieved by easing corporate financing constraints and reducing corporate en-vironmental uncertainty;and the impact of digital transformation on green innovation is geographically heterogeneous.展开更多
Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of t...Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.展开更多
Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the s...Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.展开更多
基金supported by the National Natural Science Foundation of China(72374061,72204243)the Ministry of Education’s Humanities and Social Science Research Youth Fund Project(20YJC630138,22YJC630056)+1 种基金Anhui Provincial Natural Science Foundation(2208085UD02)New Liberal Arts Fund Expansion Project of University of Science and Technology of China(FSSF-A-230317).
文摘In the era of green logistics,digital transformation has become an effective means for the logistics industry’s high-quality development.Using listed companies in China’s logistics industry from 2010 to 2021 as the research samples,this paper conducts an empirical test on the impact of the digital transformation of logistics enterprises on their green in-novation.Specifically,enterprise digital transformation indicators are constructed through the text analysis method,and the fixed-effects model is applied for analysis.The results indicate that the digital transformation of logistics enterprises has a significant promoting effect on their green innovation;the promoting effect of the digital transformation of logistics enterprises on green innovation is primarily achieved by easing corporate financing constraints and reducing corporate en-vironmental uncertainty;and the impact of digital transformation on green innovation is geographically heterogeneous.
基金Project(51178061)supported by the National Natural Science Foundation of ChinaProject(2010FJ6016)supported by Hunan Provincial Science and Technology,China+1 种基金Project(12C0015)supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(13JJ3072)supported by Hunan Provincial Natural Science Foundation of China
文摘Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.
基金This research was funded by National Natural Science Foundation of China(grant number 61473311,70901075)Natural Science Foundation of Beijing Municipality(grant number 9142017)military projects funded by the Chinese Army.
文摘Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.
