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Journal of management Science and Engineering 2024年第1期9卷 38-52页

作者： Baofeng Huo Dan Li Minhao Gu college of management and Economics Tianjin UniversityTianjin300072China

Supply chain resilience(SCR)refers to a supply chain's(SC's)ability to recover from disruptions timely and effectively.This study uses a combination of contingency and configuration approaches to examine the direct and contingent relationships between SCR dimensions(i.e.,internal,supplier,and customer resilience)and performance.It analyzes survey data collected from 206 Chinese manufacturers.The results show that the three SCR dimensions are positively related to customer satisfaction,whereas customer resilience has no direct contribution to financial performance.Internal resilience moderates the relationship between supplier resilience and performance(negative for customer satisfaction and positive for financial performance).A taxonomy for SCR was developed based on internal,supplier,and customer resilience,providing a holistic perspective for examining the performance discrepancies among four different SCR patterns:high externalleaning,high uniform,medium uniform,and low uniform.These findings offer insights for managers in building SCR from the crisis-management process.

关键词： Supply chain resilience Risk management Taxonomy Performance China

Predicting carbon storage of mixed broadleaf forests based on the finite mixture model incorporating stand factors,site quality,and aridity index

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Forest Ecosystems 2024年第3期11卷 276-286页

作者： Yanlin Wang Dongzhi Wang Dongyan Zhang Qiang Liu Yongning Li college of Forestry Hebei Agricultural UniversityBaoding071001China college of Economics and management Hebei Agricultural UniversityBaoding071001China

The diameter distribution function(DDF)is a crucial tool for accurately predicting stand carbon storage(CS).The current key issue,however,is how to construct a high-precision DDF based on stand factors,site quality,and aridity index to predict stand CS in multi-species mixed forests with complex structures.This study used data from70 survey plots for mixed broadleaf Populus davidiana and Betula platyphylla forests in the Mulan Rangeland State Forest,Hebei Province,China,to construct the DDF based on maximum likelihood estimation and finite mixture model(FMM).Ordinary least squares(OLS),linear seemingly unrelated regression(LSUR),and back propagation neural network(BPNN)were used to investigate the influences of stand factors,site quality,and aridity index on the shape and scale parameters of DDF and predicted stand CS of mixed broadleaf forests.The results showed that FMM accurately described the stand-level diameter distribution of the mixed P.davidiana and B.platyphylla forests;whereas the Weibull function constructed by MLE was more accurate in describing species-level diameter distribution.The combined variable of quadratic mean diameter(Dq),stand basal area(BA),and site quality improved the accuracy of the shape parameter models of FMM;the combined variable of Dq,BA,and De Martonne aridity index improved the accuracy of the scale parameter models.Compared to OLS and LSUR,the BPNN had higher accuracy in the re-parameterization process of FMM.OLS,LSUR,and BPNN overestimated the CS of P.davidiana but underestimated the CS of B.platyphylla in the large diameter classes(DBH≥18 cm).BPNN accurately estimated stand-and species-level CS,but it was more suitable for estimating stand-level CS compared to species-level CS,thereby providing a scientific basis for the optimization of stand structure and assessment of carbon sequestration capacity in mixed broadleaf forests.

关键词： Weibull function Finite mixture model Linear seemingly unrelated regression Back propagation neural network Carbon storage

A dynamic exploratory hybrid modelling framework for simulating complex and uncertain system

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Journal of Safety Science and Resilience 2024年第2期5卷 167-178页

作者： Gangqiao Wang Han Xing Yongqiang Chen Yi Liu Institute of Big Data Inteligent management and Decision-making College of ManagementShenzhen UniversityShenzhen 518060China School of Safety Science Tsinghua UniversityBejing 100084China Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBejing 100871China

Complex disaster systems involve various components and mechanisms that could interact in complex ways and change over time,leading to significant deep uncertainty.Due to deep uncertainty,decision-makers have severe inadequacy of knowledge and often encounter unpredictable surprises that may emerge in the future,thus making it difficult to specify appropriate models and parameters to describe the system of interest.In this paper,we propose a dynamic exploratory hybrid modeling framework that fits data,models,and computational ex-periments together to simulate complex systems with deep uncertainty.In the framework,one needs to develop multiple plausible models from a hybrid modeling perspective and perform enormous computational experi-ments to explore the diversity of future scenarios.Real-time data is then incorporated into diverse forecasts to dynamically adjust the simulation system.This ultimately enables an ongoing modeling and analysis process in which deep uncertainty would be gradually mitigated.Our approach has been applied to a human-involved car-following system simulation under complex traffic conditions.The results show that the proposed approach can improve the prediction accuracy while enhancing the sensitivity of the simulation system to uncertain changes in the system of interest.

关键词： Disaster modeling and analysis Deepuncertainty Hybrid modeling Adaptivesimulation

A Superior Sales Mode for a Two-Echelon Supply Chain of Perishable Products

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Journal of Systems Science and Information 2024年第2期12卷 274-293页

作者： Mengqi BAO Xiaozhen DAI School of management Wenzhou Business CollegeWenzhou 325035China

This paper considers sales mode selection issues for a two-echelon supply chain of perishable products involving a supplier and a retailer.Consumers’purchase desire is assumed to be positive correlation with the freshness of the product.First,the traditional sales mode is examined,in which the supplier and the retailer play a Stackelberg game.We propose a three-layer decision model for this situation,and obtain dynamic pricing strategies and selling cycle length.It is shown that the retailer has little motivation to order many perishable products so as to avoid a long selling cycle length.Second,the commission-charge mode is analyzed,in which the retailer declares its decision first.In this mode,we demonstrate that the perishable product will be on sale during the whole shelf life under a certain condition.The correlation between the sales price of each stage and the remaining shelf-life length is analyzed.Third,the superiority analysis for the two sales modes is conducted.We show the relation between the selling cycle lengths of the two modes.By our analysis,it is shown that both the supplier and the retailer gain more profits when the commission-charge mode is adopted and the commission rate locates in a certain open interval.Finally,a numerical illustration is presented to visualize the discussed models,and some supplements are made for the acquired conclusions by the illustration.

关键词： pricing sales mode commission-charge mode selling cycle length superiority analysis

Dynamic control of a firm’s process innovation with knowledge accumulation in a vertically differentiated monopoly

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Journal of management Analytics 2024年第1期11卷 1-25页

作者： Shoude Li Antai college of Economics and management Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

This paper explores a multiproduct firm’s process innovation of high-and lowquality goods with knowledge accumulation in a vertically differentiated monopoly.We show that:(i)the system admits a saddle-point steady-state equilibrium under firm decision-making and social planner adjustment,respectively;(ii)the firm’s learning rates of knowledge accumulation of process innovation call for more intense efforts in both directions;(iii)there is a substitution between the process innovation for these two kinds of goods;(iv)the social incentive towards both kinds of innovation efforts is always larger than the private incentive characterizing the profit-seeking firm.Our contribution extends the dynamic innovation literature that focuses on singlegood and considers the effects of corresponding knowledge accumulation on process innovation of these two kinds of goods.Further,this theoretical work contributes to the design of efficient innovation effort strategies for firms’process innovation with corresponding knowledge accumulation in a vertically differentiated monopoly market.

关键词： process innovation knowledge accumulation high-quality good low-quality good

Antigen epitopes of animal coronaviruses:a mini-review

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Animal Diseases 2024年第1期4卷 19-26页

作者： Mingjun Su Guanghui Zheng Xiangwen Xu Houhui Song Key Laboratory of Applied Technology On Green-Eco-healthy Animal Husbandry of Zhejiang Province Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics&Advanced TechnologyZhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health ManagementChina-Australia Joint Laboratory for Animal Health Big Data AnalyticsCollege of Animal Science and Technology&College of Veterinary Medicine of ZhejiangA&F University666 Wusu StreetLin'an DistrictHangzhou 311300Zhejiang ProvinceChina

Coronaviruses are widespread in nature and can infect mammals and poultry,making them a public health concern.Globally,prevention and control of emerging and re-emerging animal coronaviruses is a great challenge.The mecha-nisms of virus-mediated immune responses have important implications for research on virus prevention and control.The antigenic epitope is a chemical group capable of stimulating the production of antibodies or sensitized lympho-cytes,playing an important role in antiviral immune responses.Thus,it can shed light on the development of diagnos-tic methods and novel vaccines.Here,we have reviewed advances in animal coronavirus antigenic epitope research,aiming to provide a reference for the prevention and control of animal and human coronaviruses.

关键词： Animal coronavirus Antigen epitope B-cell epitope T-cell epitope Immune responses Vaccines

Performance evaluation of seven multi-label classification methods on real-world patent and publication datasets

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Journal of Data and Information Science 2024年第2期9卷 81-103页

作者： Shuo Xu Yuefu Zhang Xin An Sainan Pi college of Economics and management Beijing University of TechnologyBeijing 100124China School of Economics&management Beijing Forestry UniversityBeijing 100083China

Purpose:Many science,technology and innovation(STI)resources are attached with several different labels.To assign automatically the resulting labels to an interested instance,many approaches with good performance on the benchmark datasets have been proposed for multi-label classification task in the literature.Furthermore,several open-source tools implementing these approaches have also been developed.However,the characteristics of real-world multi-label patent and publication datasets are not completely in line with those of benchmark ones.Therefore,the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world datasets.Research limitations:Three real-world datasets differ in the following aspects:statement,data quality,and purposes.Additionally,open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection,which in turn impacts the performance of a multi-label classification approach.In the near future,we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter settings.Practical implications:The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets,underscoring the complexity of real-world multi-label classification tasks.Approaches leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among labels.With ongoing enhancements in deep learning algorithms and large-scale models,it is expected that the efficacy of multi-label classification tasks will be significantly improved,reaching a level of practical utility in the foreseeable future.Originality/value:(1)Seven multi-label classification methods are comprehensively compared on three real-world datasets.(2)The TextCNN and TextRCNN models perform better on small-scale da

关键词： Multi-label classification Real-World datasets Hierarchical structure Classification system Label correlation Machine learning

Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach

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Computers, Materials & Continua 2024年第2期78卷 2557-2573页

作者： Dayu Xu Jiaming Lu Xuyao Zhang Hongtao Zhang college of Mathematics and Computer Science Zhejiang A&F UniversityHangzhou311300China college of Economics and management Zhejiang A&F UniversityHangzhou311300China

Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.

关键词： Data stream clustering TEDA KD-tree scapegoat tree

Coupling and coordinated evolution characteristics of regional economy-energy-carbon emission multiple systems:A case study of main China's Basin

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Journal of Environmental Sciences 2024年第6期140卷 204-218页

作者： Lu Chen Xin Li Jingyi Zhao Xinyu Kang Lu Liu Minxi Wang Wu Chen college of management Science Chengdu University of TechnologyChengdu 610051China SDU Life Cycle Engineering Department of Green TechnologyUniversity of Southern Denmark5230 OdenseDenmark

Comprehensive analysis of the Economy-Energy-Carbon Emission(EECE)system is beneficial for promoting sustainable social development.This study analyzes the system development of major watersheds in China from 2010 to 2019.The research fully considers the system’s internal and external inputs and outputs and proposes an evaluation index system for regional EECE coupling and coordinated development.Then,using the difference in system weight allocation to improve the coupling and coordination model,the study explores the dynamic system’s coupling and coordination.The results show that(1)The development of the system structure is relatively stable,but the overall development status is not ideal;(2)The downstream of China’s main river basins has obvious economic advantages,while the energy system fluctuates greatly.The efficiency of the carbon emission system will decrease in areas with rapid economic development.The coupling and coordination level of the EECE system is better in the Yangtze River Basin than in the Yellow River Basin;(3)From the perspective of dynamic coordinated development,the main river basins have been divided into two states since 2012,but it is relatively stable overall.Regional dynamic coordination is often at a disadvantage in regions with rapid economic and energy development;(4)The coupling coordination degree of the two river basins has significant positive spatial autocorrelation.Most provinces’significant spatial clustering characteristics of the coupling coordination degree are High-High type.Low-Low type provinces are mainly concentrated downstream.The research process has certain reference significance for the collaborative governance of complex regional systems.

关键词： System structure Efficiency measure Coupling mechanism Dynamic coordination

Women’s empowerment and food consumption:Evidence from female-headed households in Tanzania

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Journal of Integrative Agriculture 2024年第2期23卷 457-467页

作者： Mosses Lufuke Xu Tian college of Economics and management Nanjing Agricultural UniversityNanjing 210095China Department of Economics The University of DodomaDodoma 41218Tanzania college of Economics and management China Agricultural UniversityBeijing 100083China Academy of Global Food Economics and Policy China Agricultural UniversityBeijing 100083China

Despite the growing recognition of women’s increasing role in the household and corresponding empowerment programs in sub-Saharan Africa,intensive research on the relationship between women’s influence and household food consumption is minimal.Using the most recent(2017-2018)national household survey data from Tanzania,this study examined the influence of women’s empowerment on household food consumption.First,we compared the monthly consumption of eight food categories between female-headed households(FHHs)and male-headed households(MHHs)using both descriptive statistics and the propensity score matching(PSM)method.Furthermore,we adopted the two-stage Linear Expenditure System and Almost Ideal Demand System model(LES-AIDS)to estimate income and price elasticities for the two household types.The results show that FHHs consume bread and cereals,fish,oils and fats,vegetables,and confectionery(sugar,jam,honey,chocolate,etc.)more than MHHs.Moreover,FHHs have a significantly higher income elasticity of demand for all food groups than MHHs.They are also more price elastic than MHHs in meat,fish,oils,fats,sugar,jam,honey,chocolate,etc.

关键词： women’s empowerment food consumption income elasticity price elasticity