{"title":"Spatial disparities in risk management in China: application of the theory of planned behavior","authors":"Xinyu Jiang, Xiaotong Wang, Yingying Sun, Lijiao Yang, Zuheng Lv, Subhajyoti Samaddar","doi":"10.1007/s44176-024-00027-w","DOIUrl":"https://doi.org/10.1007/s44176-024-00027-w","url":null,"abstract":"","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139850381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatial disparities in risk management in China: application of the theory of planned behavior","authors":"Xinyu Jiang, Xiaotong Wang, Yingying Sun, Lijiao Yang, Zuheng Lv, Subhajyoti Samaddar","doi":"10.1007/s44176-024-00027-w","DOIUrl":"https://doi.org/10.1007/s44176-024-00027-w","url":null,"abstract":"","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":" 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139790420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction: Cooperation dynamics in public goods games with evolving cognitive bias","authors":"Ji Quan, Haoze Li, Xianjia Wang","doi":"10.1007/s44176-024-00026-x","DOIUrl":"https://doi.org/10.1007/s44176-024-00026-x","url":null,"abstract":"","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"16 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139598530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A novel technique for solving intuitionistic fuzzy DEA model: an application in Indian agriculture sector","authors":"Kshitish Kumar Mohanta, Deena Sunil Sharanappa","doi":"10.1007/s44176-023-00022-7","DOIUrl":"https://doi.org/10.1007/s44176-023-00022-7","url":null,"abstract":"Abstract Fuzzy DEA is a performance measurement tool that is used to assess the performance of DMUs in highly uncertain environments. In this article, the Intuitionistic fuzzy DEA (IFDEA) model is proposed based on the triangular intuitionistic fuzzy numbers (TIFNs). The weighted Possibility mean for TIFN is used to compare and rank the TIFN. The weighted possibility mean approach is proposed to solve the IFDEA model, and the IFDEA model is converted into its equivalent crisp DEA model to assess the relative efficiencies of the DMUs. One advantage of the proposed approach is that the attitude of the decision-maker is considered while measuring the efficiency of the DMUs. The weight or risk factor $$delta in [0,1]$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>[</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> indicates whether the decision-maker is a risk-taker, neutral, or adverse. The crisp DEA model is a LP problem that is solved by using an existing LP method with different risk factors to determine the efficiency score of the DMUs. The DMUs are ranked based on the overall efficiency score of the DMUs, which is the arithmetic mean of the efficiency scores of the DMUs with different risk factors. Two numerical examples are given here to demonstrate the validity and applicability of the proposed technique and to compare the performance of the DMUs in the proposed approach with the exciting ranking approach and the expected value approach. A case study on the agriculture sector has been conducted in order to evaluate the agricultural performance of Indian states using the IFDEA model. According to the results of the IFDEA model, 15 (53.57%) out of the 28 Indian states were found to be efficient.","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"57 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135934550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiali Fu, Yuqian Shi, Yujia Hu, Yue Ming, Bipan Zou
{"title":"Location optimization of on-campus bicycle-sharing electronic fences","authors":"Jiali Fu, Yuqian Shi, Yujia Hu, Yue Ming, Bipan Zou","doi":"10.1007/s44176-023-00020-9","DOIUrl":"https://doi.org/10.1007/s44176-023-00020-9","url":null,"abstract":"Abstract In the bicycle-sharing operation network, the mismatch between supply and demand as well as indiscriminate bicycle parking have caused the waste of resources and increased management costs for operators. This study presents design of a bike-sharing electronic fences location developed for Hunan University of Technology and Business. In this paper, we constructed Site Selection Model with Constrained Service Level and use Hybrid Genetic & Annealing algorithm (HGAA) to adjust the location of electronic fences to balance the supply and demand of sharing bicycles with the objective function of minimizing the cost and ensuring the service level, and we use Hunan University of Technology and Industry as an example to verify the effectiveness of the method.","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"76 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136106011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jian Min, Zhi-Qi Li, Yi Liu, Yu-Dan Zhang, Jian-Bo Yang
{"title":"Automotive manufacturing enterprise financial risk evolution monitoring and early warning simulation: based on the perspective of value chain analysis","authors":"Jian Min, Zhi-Qi Li, Yi Liu, Yu-Dan Zhang, Jian-Bo Yang","doi":"10.1007/s44176-023-00021-8","DOIUrl":"https://doi.org/10.1007/s44176-023-00021-8","url":null,"abstract":"Abstract The automotive industry value chain, which includes the “upstream suppliers—the middle-stream manufacturing enterprises-downstream customers”, constitutes the closest environment for the automotive manufacturing enterprises. From the perspective of value chain, combined with the idea of system dynamics, we analyze the formation mechanism of financial risk in automotive manufacturing enterprises, construct a financial risk evolution monitoring model based on value stream and construct a financial dynamic early warning simulation model by using free cash flow. The vehicle manufacturing listed companies in 2011–2015 are selected as samples. The empirical research results show that the financial risk situation can be changed by adjusting the value chain structure, that is, the causal feedback of the system, and the result of financial warning may change. The contribution of this paper is to analyze the enterprise financial risk based on the value chain and provide new ideas for the financial early warning of the enterprise from the perspective of value creation.","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"26 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Joint advertising and ordering decisions under the pre-sales crowdfunding","authors":"Kuan Zeng, Yaohan Shen","doi":"10.1007/s44176-023-00018-3","DOIUrl":"https://doi.org/10.1007/s44176-023-00018-3","url":null,"abstract":"Abstract Our study considers a company launching new product on pre-sales crowdfunding platform and explores the joint advertising and ordering decisions in mass market thereafter. Under the “AON” mechanism, we construct profit-maximizing models to examine the impact of pledged amount on the company’s decision on advertising expense, order quantity and funding target. The results show that the optimal order quantity increases with the pledged amount in crowdfunding, and the company won’t promote new product in mass market until the pledged amount reaches a funding threshold, and the advertising expense increases with the pledged amount since then. In addition, we figure out the feasible scope for the funding target and suggest the company set the target within the scope, to ensure the project profitability. Furthermore, we demonstrate that the expected pledged amount won’t increase with the funding target, and the optimal funding target would be the lower bound in its feasible scope, to improve the campaign success. Finally, we conduct numerical analysis to verify our theoretical results.","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136313403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yifeng Tang, Fan Xu, Lu Xu, Chao Zhou, Yaling Deng
{"title":"Remain useful life forecasting for roller bearings using sparse auto-encoder","authors":"Yifeng Tang, Fan Xu, Lu Xu, Chao Zhou, Yaling Deng","doi":"10.1007/s44176-023-00019-2","DOIUrl":"https://doi.org/10.1007/s44176-023-00019-2","url":null,"abstract":"Abstract A method based on sparse auto-encoder (SAE) in deep learning (DL) for roller bearings remain useful life (RUL) prediction is presented in this paper. Firstly, the roller bearings vibration signals were calculated by different time and frequency domain factors, in which reflect the vibration signals information well. Therefore, the time and frequency domain features were regarded as the input of SAE, then the SAE model in deep learning was used to extract the features through several hidden layers and the sigmoid function was selected as the output function for calculate the prediction value. Finally, compared with other different prediction methods, such as support vector machine (SVM), back propagation (BP) neural network and random forest (RF), the performance of SAE is better than that those models by using mean absolute error (MAE) and root mean square error (RMSE) these two indicators.","PeriodicalId":481522,"journal":{"name":"Management System Engineering","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134912441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}