Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-533-16
S. Mao, Bin Liu, Yimin Shi
Abstract This paper investigates a simple step-stress accelerated lifetime test (SSALT) model for the inferential analysis of exponential competing risks data. A generalized type-I hybrid censoring scheme is employed to improve the efficiency and controllability of the test. Firstly, the MLEs for parameters are established based on the cumulative exposure model (CEM). Then the conditional moment generating function (MGF) for unknown parameters is set up using conditional expectation and multiple integral techniques. Thirdly, confidence intervals (CIs) are constructed by the exact MGF-based method, the approximate normality-based method, and the bias-corrected and accelerated (BCa) percentile bootstrap method. Finally, we present simulation studies and an illustrative example to compare the performances of different methods.
{"title":"Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-I Hybrid Censoring","authors":"S. Mao, Bin Liu, Yimin Shi","doi":"10.21078/JSSI-2021-533-16","DOIUrl":"https://doi.org/10.21078/JSSI-2021-533-16","url":null,"abstract":"Abstract This paper investigates a simple step-stress accelerated lifetime test (SSALT) model for the inferential analysis of exponential competing risks data. A generalized type-I hybrid censoring scheme is employed to improve the efficiency and controllability of the test. Firstly, the MLEs for parameters are established based on the cumulative exposure model (CEM). Then the conditional moment generating function (MGF) for unknown parameters is set up using conditional expectation and multiple integral techniques. Thirdly, confidence intervals (CIs) are constructed by the exact MGF-based method, the approximate normality-based method, and the bias-corrected and accelerated (BCa) percentile bootstrap method. Finally, we present simulation studies and an illustrative example to compare the performances of different methods.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125883401","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}
Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-549-09
Lina Wang, K. Milis, S. Poelmans
Abstract Pollution cost control is key to solve pollution problem. The paper takes pollution control cost of pollution control contract between management authority and pollutant discharge enterprise as research object, considers pollution control quality level, pollution control quality inspection and pollution control cost model, and establishes pollution control cost model of management authority and pollutant discharge enterprise, including rational constraints of pollutant discharge enterprise. And it analyzes principal-agent relationship between the two under condition of asymmetric information, and un-observability of pollution control level is shown as hiding information of sewage enterprises. In essence, it is problem of adverse selection in principal-agent. Pollution control cost of management is objective function. The first order condition of pollution control cost of sewage enterprise is transformed into state space equation, and optimal control of problem is solved by using maximum principle. In particular, management authority, as principal, uses pollution control provisions to reward, punish and encourage pollutant discharge enterprises as agents.
{"title":"Study on Pollution Cost Control Model under Asymmetric Information Based on Principal Agent","authors":"Lina Wang, K. Milis, S. Poelmans","doi":"10.21078/JSSI-2021-549-09","DOIUrl":"https://doi.org/10.21078/JSSI-2021-549-09","url":null,"abstract":"Abstract Pollution cost control is key to solve pollution problem. The paper takes pollution control cost of pollution control contract between management authority and pollutant discharge enterprise as research object, considers pollution control quality level, pollution control quality inspection and pollution control cost model, and establishes pollution control cost model of management authority and pollutant discharge enterprise, including rational constraints of pollutant discharge enterprise. And it analyzes principal-agent relationship between the two under condition of asymmetric information, and un-observability of pollution control level is shown as hiding information of sewage enterprises. In essence, it is problem of adverse selection in principal-agent. Pollution control cost of management is objective function. The first order condition of pollution control cost of sewage enterprise is transformed into state space equation, and optimal control of problem is solved by using maximum principle. In particular, management authority, as principal, uses pollution control provisions to reward, punish and encourage pollutant discharge enterprises as agents.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114822953","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}
Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-469-29
Ping Li, Jie Li, Ziyi Zhang
Abstract In this paper, we apply the structural vector autoregression (SVAR) model to decompose the international oil price shock into oil supply shocks, aggregate demand shocks and oil-specific demand shocks, and then use the DCC-GARCH model to analyse the dynamic correlations between these three kinds of oil price shocks and the macroeconomic variables of several oil importing and exporting countries. To quantify the intensity of the effect of oil shocks on these variables, we propose a measure, conditional expectation (CoE), to capture the percent change of the economic variable under oil price shocks relative to the median state. The time-varying copula model is employed to estimate the proposed measure through time. The empirical results show that, for instance, the impacts of oil price shocks on macroeconomic variables are different in different periods, showing the time-varying characteristics. Additionally, the impacts of oil price shocks on macroeconomic variables show great differences and some similarities among different countries. Finally, we give some policy suggestions for these countries, in particular for China’s special results.
{"title":"The Dynamic Impact of Structural Oil Price Shocks on the Macroeconomy","authors":"Ping Li, Jie Li, Ziyi Zhang","doi":"10.21078/JSSI-2021-469-29","DOIUrl":"https://doi.org/10.21078/JSSI-2021-469-29","url":null,"abstract":"Abstract In this paper, we apply the structural vector autoregression (SVAR) model to decompose the international oil price shock into oil supply shocks, aggregate demand shocks and oil-specific demand shocks, and then use the DCC-GARCH model to analyse the dynamic correlations between these three kinds of oil price shocks and the macroeconomic variables of several oil importing and exporting countries. To quantify the intensity of the effect of oil shocks on these variables, we propose a measure, conditional expectation (CoE), to capture the percent change of the economic variable under oil price shocks relative to the median state. The time-varying copula model is employed to estimate the proposed measure through time. The empirical results show that, for instance, the impacts of oil price shocks on macroeconomic variables are different in different periods, showing the time-varying characteristics. Additionally, the impacts of oil price shocks on macroeconomic variables show great differences and some similarities among different countries. Finally, we give some policy suggestions for these countries, in particular for China’s special results.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122184508","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}
Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-498-21
Chenglin Shen, Xinxin Zhang
Abstract Given consumers’ trade-offs between conventional economic and environmental attributes of products, we provide a game-theoretic model to explore the role of GTA strategy in duopoly competition by incorporating two salient features: Two product types — The green product produced by a firm with GTA strategy and the ordinary product produced by a firm without GTA strategy, and two consumer segments, i.e., the green consumers who are willing to pay for green products and the ordinary consumers who are willing to pay for ordinary products. Our analysis shows that GTA strategy may either increase or decrease the green firm’s quality provision. The subtle relationship between the green firm’s quality strategy and GTA strategy not only affects its own equilibrium performances but its rival’s. We also find that two consumer segments may be better off in the presence of a lower GTA intensity. Additionally, although the GTA strategy benefits the environment, the GTA investment is not the more the better. Finally, we find that GTA strategy would lead to higher social welfare only when the GTA efficiency is high enough. Our work not only provides an alternative economic explanation why some firms choose to implement GTA strategy and some do not in reality, but gives managerial insights for firms with different GTA strategies as well as policy insights for the social planner.
{"title":"The Effect of Green Technology Adoption Strategy on Duopoly Competition","authors":"Chenglin Shen, Xinxin Zhang","doi":"10.21078/JSSI-2021-498-21","DOIUrl":"https://doi.org/10.21078/JSSI-2021-498-21","url":null,"abstract":"Abstract Given consumers’ trade-offs between conventional economic and environmental attributes of products, we provide a game-theoretic model to explore the role of GTA strategy in duopoly competition by incorporating two salient features: Two product types — The green product produced by a firm with GTA strategy and the ordinary product produced by a firm without GTA strategy, and two consumer segments, i.e., the green consumers who are willing to pay for green products and the ordinary consumers who are willing to pay for ordinary products. Our analysis shows that GTA strategy may either increase or decrease the green firm’s quality provision. The subtle relationship between the green firm’s quality strategy and GTA strategy not only affects its own equilibrium performances but its rival’s. We also find that two consumer segments may be better off in the presence of a lower GTA intensity. Additionally, although the GTA strategy benefits the environment, the GTA investment is not the more the better. Finally, we find that GTA strategy would lead to higher social welfare only when the GTA efficiency is high enough. Our work not only provides an alternative economic explanation why some firms choose to implement GTA strategy and some do not in reality, but gives managerial insights for firms with different GTA strategies as well as policy insights for the social planner.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124052978","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}
Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-519-14
Shengxia Xu, Qiang Liu, Xiaoli Lu
Abstract We develop a statistical framework to use the data of night-time-lights (DN) from satellite to augment official GDP measures, and a non-linear substitution relationship between DN and GDP is given. In this paper, we take advantage of DN instead of GDP to measure the imbalance of regional development (IRD) in China by using the method of bi-dimensional decomposition under the population-weighted coefficient of variation. The method enables us to analyze the contributions of DN components to within-region and between-regions inequality under the framework which has been proposed, we can get the conclusion that the imbalance between-regions rather than within-region is the main reason for the influence of IRD for the whole country in China.
{"title":"Measuring the Imbalance of Regional Development from Outer Space in China","authors":"Shengxia Xu, Qiang Liu, Xiaoli Lu","doi":"10.21078/JSSI-2021-519-14","DOIUrl":"https://doi.org/10.21078/JSSI-2021-519-14","url":null,"abstract":"Abstract We develop a statistical framework to use the data of night-time-lights (DN) from satellite to augment official GDP measures, and a non-linear substitution relationship between DN and GDP is given. In this paper, we take advantage of DN instead of GDP to measure the imbalance of regional development (IRD) in China by using the method of bi-dimensional decomposition under the population-weighted coefficient of variation. The method enables us to analyze the contributions of DN components to within-region and between-regions inequality under the framework which has been proposed, we can get the conclusion that the imbalance between-regions rather than within-region is the main reason for the influence of IRD for the whole country in China.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121019945","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}
Pub Date : 2021-10-01DOI: 10.21078/JSSI-2021-558-17
Kai Wang, Fuzhi Wang
Abstract The topic recognition for dynamic topic number can realize the dynamic update of super parameters, and obtain the probability distribution of dynamic topics in time dimension, which helps to clear the understanding and tracking of convection text data. However, the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge. Therefore, it is impossible to deeply perceive the dynamic change of the topic in the time series. By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation model, a topic feature lattice under the dynamic topic number is constructed. In the model, documents, topics and vocabularies are jointly modeled to generate two probability distribution matrices: Documents-topics and topic-feature words. Afterwards, the association intensity is computed between the topic and its feature vocabulary to establish the topic formal context matrix. Finally, the topic feature is induced according to the formal concept analysis (FCA) theory. The topic feature lattice under dynamic topic number (TFL_DTN) model is validated on the real dataset by comparing with the mainstream methods. Experiments show that this model is more in line with actual needs, and achieves better results in semi-automatic modeling of topic visualization analysis.
{"title":"Topic-Feature Lattices Construction and Visualization for Dynamic Topic Number","authors":"Kai Wang, Fuzhi Wang","doi":"10.21078/JSSI-2021-558-17","DOIUrl":"https://doi.org/10.21078/JSSI-2021-558-17","url":null,"abstract":"Abstract The topic recognition for dynamic topic number can realize the dynamic update of super parameters, and obtain the probability distribution of dynamic topics in time dimension, which helps to clear the understanding and tracking of convection text data. However, the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge. Therefore, it is impossible to deeply perceive the dynamic change of the topic in the time series. By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation model, a topic feature lattice under the dynamic topic number is constructed. In the model, documents, topics and vocabularies are jointly modeled to generate two probability distribution matrices: Documents-topics and topic-feature words. Afterwards, the association intensity is computed between the topic and its feature vocabulary to establish the topic formal context matrix. Finally, the topic feature is induced according to the formal concept analysis (FCA) theory. The topic feature lattice under dynamic topic number (TFL_DTN) model is validated on the real dataset by comparing with the mainstream methods. Experiments show that this model is more in line with actual needs, and achieves better results in semi-automatic modeling of topic visualization analysis.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128540501","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}
Pub Date : 2021-08-01DOI: 10.21078/JSSI-2021-399-22
Weiguo Chen, Shufen Zhou, Yin Zhang, Yi Sun
Abstract According to behavioral finance theory, investor sentiment generally exists in investors’ trading activities and influences financial market. In order to investigate the interaction between investor sentiment and stock market as well as financial industry, this study decomposed investor sentiment, stock price index and SWS index of financial industry into IMF components at different scales by using BEMD algorithm. Moreover, the fluctuation characteristics of time series at different time scales were extracted, and the IMF components were reconstructed into short-term high-frequency components, medium-term important event low-frequency components and long-term trend components. The short-term interaction between investor sentiment and Shanghai Composite Index, Shenzhen Component Index and financial industries represented by SWS index was investigated based on the spillover index. The time difference correlation coefficient was employed to determine the medium-term and long-term correlation among variables. Results demonstrate that investor sentiment has a strong correlation with Shanghai Composite Index, Shenzhen Component Index and different financial industries represented by SWS index at the original scale, and the change of investor sentiment is mainly influenced by external market information. The interaction between most markets at the short-term scale is weaker than that at the original scale. Investor sentiment is more significantly correlated with SWS Bond, SWS Diversified Finance and Shanghai Composite Index at the long-term scale than that at the medium-term scale.
{"title":"A Study of Multi-Scale Relationship Between Investor Sentiment and Stock Index Fluctuation Based on the Analysis of BEMD Spillover Index","authors":"Weiguo Chen, Shufen Zhou, Yin Zhang, Yi Sun","doi":"10.21078/JSSI-2021-399-22","DOIUrl":"https://doi.org/10.21078/JSSI-2021-399-22","url":null,"abstract":"Abstract According to behavioral finance theory, investor sentiment generally exists in investors’ trading activities and influences financial market. In order to investigate the interaction between investor sentiment and stock market as well as financial industry, this study decomposed investor sentiment, stock price index and SWS index of financial industry into IMF components at different scales by using BEMD algorithm. Moreover, the fluctuation characteristics of time series at different time scales were extracted, and the IMF components were reconstructed into short-term high-frequency components, medium-term important event low-frequency components and long-term trend components. The short-term interaction between investor sentiment and Shanghai Composite Index, Shenzhen Component Index and financial industries represented by SWS index was investigated based on the spillover index. The time difference correlation coefficient was employed to determine the medium-term and long-term correlation among variables. Results demonstrate that investor sentiment has a strong correlation with Shanghai Composite Index, Shenzhen Component Index and different financial industries represented by SWS index at the original scale, and the change of investor sentiment is mainly influenced by external market information. The interaction between most markets at the short-term scale is weaker than that at the original scale. Investor sentiment is more significantly correlated with SWS Bond, SWS Diversified Finance and Shanghai Composite Index at the long-term scale than that at the medium-term scale.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127265877","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}
Abstract The influence of taxation on the economy and society is everywhere. Given the fact that CO2 emission is closely connected with human activities, the question naturally arises whether the tax burden affects the carbon emissions. To address this issue, based on the data of 21 OECD countries over the period from 1991–2014, we use the ratio of tax revenue to GDP as a proxy of the tax burden and employ a panel quantile model with the non-additive fixed effects for analysis. The results suggest that the impact of the tax burden on carbon emissions is heterogeneous across countries based on the level of carbon emissions. Moreover, we find a stable U-shaped relationship between the tax burden and carbon emissions whether for countries with a high or low level of carbon emissions. Our findings suggest that moderate taxes could help reduce carbon emissions, but the effect of excessive taxation is the opposite.
{"title":"Will Tax Burden Be a Stumbling Block to Carbon-Emission Reduction? Evidence from OECD Countries","authors":"Yishuai Ren, Yong Jiang, Chao-qun Ma, Jiang-Long Liu, Jing Chen","doi":"10.21078/JSSI-2021-335-21","DOIUrl":"https://doi.org/10.21078/JSSI-2021-335-21","url":null,"abstract":"Abstract The influence of taxation on the economy and society is everywhere. Given the fact that CO2 emission is closely connected with human activities, the question naturally arises whether the tax burden affects the carbon emissions. To address this issue, based on the data of 21 OECD countries over the period from 1991–2014, we use the ratio of tax revenue to GDP as a proxy of the tax burden and employ a panel quantile model with the non-additive fixed effects for analysis. The results suggest that the impact of the tax burden on carbon emissions is heterogeneous across countries based on the level of carbon emissions. Moreover, we find a stable U-shaped relationship between the tax burden and carbon emissions whether for countries with a high or low level of carbon emissions. Our findings suggest that moderate taxes could help reduce carbon emissions, but the effect of excessive taxation is the opposite.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"54 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132628840","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}
Pub Date : 2021-08-01DOI: 10.21078/JSSI-2021-455-14
Qi Suo, Liyuan Wang, Tianzi Yao, Zihao Wang
Abstract Understanding the causation of accidents is essential to promote metro operation safety. In terms of 243 reported metro operation accident cases in China, a directed weighted network was constructed based on complex network theory, where nodes and directed edges denotes factors and event chains respectively. To reveal the key causal factors, the topological characteristics of metro operation accident network (MOAN) were analyzed from both global and local views. The results show that facility-type factors are more closely related to the occurrence of the accidents from the perspectives of average path length and cascading effects. Accident types like train delay and train suspension are the great risk recipients. Key causal factors with large out-degree, out-strength, betweenness centrality and cluster coefficient, such as communication and signal failure, vehicle failure and piling into the train should be noticed. The research framework proposed in the paper is not only applicable to China’s metro operation system, but also appropriate for other transportation system safety studies.
{"title":"Promoting Metro Operation Safety by Exploring Metro Operation Accident Network","authors":"Qi Suo, Liyuan Wang, Tianzi Yao, Zihao Wang","doi":"10.21078/JSSI-2021-455-14","DOIUrl":"https://doi.org/10.21078/JSSI-2021-455-14","url":null,"abstract":"Abstract Understanding the causation of accidents is essential to promote metro operation safety. In terms of 243 reported metro operation accident cases in China, a directed weighted network was constructed based on complex network theory, where nodes and directed edges denotes factors and event chains respectively. To reveal the key causal factors, the topological characteristics of metro operation accident network (MOAN) were analyzed from both global and local views. The results show that facility-type factors are more closely related to the occurrence of the accidents from the perspectives of average path length and cascading effects. Accident types like train delay and train suspension are the great risk recipients. Key causal factors with large out-degree, out-strength, betweenness centrality and cluster coefficient, such as communication and signal failure, vehicle failure and piling into the train should be noticed. The research framework proposed in the paper is not only applicable to China’s metro operation system, but also appropriate for other transportation system safety studies.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115039497","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}
Pub Date : 2021-08-01DOI: 10.21078/JSSI-2021-440-15
Juan Li, Yu Zhang
Abstract Crowdsourcing task assignment has become an important task assignment model in the Internet economy era. In this paper, we study the crowdsourcing task assignment problem based on employer net profit and employee satisfaction. First, the reliability and interest of employees are modeled, based on which the mathematical expressions for employer net profit and employee satisfaction are given. Then, a multi-objective optimization problem is formulated to maximize employer net profit and employee satisfaction by jointly optimizing the task assignment matrix and task offer vector. Since the considered problem contains discrete variables, it cannot be solved directly by traditional optimization methods. Therefore, two low-complexity high-performance algorithms are proposed. The first algorithm is based on a fast non-dominated ranking genetic algorithm with an elite, which is able to explore the Pareto bound of the considered problem. The second algorithm is based on a reinforcement learning framework, which is able to maximize the weighted sum of employer net profit and employee satisfaction. Numerical results show that the number of tasks assigned to employees affects both employee satisfaction and employer net profit. The Pareto bounds and Pareto optimal solutions based on the solutions of the two proposed algorithms are also presented numerically, which quantitatively characterize the tradeoff between employer net profit and employee satisfaction.
{"title":"Crowdsourcing Task Assignment Mechanism Based on Employer Net Profit and Employee Satisfaction","authors":"Juan Li, Yu Zhang","doi":"10.21078/JSSI-2021-440-15","DOIUrl":"https://doi.org/10.21078/JSSI-2021-440-15","url":null,"abstract":"Abstract Crowdsourcing task assignment has become an important task assignment model in the Internet economy era. In this paper, we study the crowdsourcing task assignment problem based on employer net profit and employee satisfaction. First, the reliability and interest of employees are modeled, based on which the mathematical expressions for employer net profit and employee satisfaction are given. Then, a multi-objective optimization problem is formulated to maximize employer net profit and employee satisfaction by jointly optimizing the task assignment matrix and task offer vector. Since the considered problem contains discrete variables, it cannot be solved directly by traditional optimization methods. Therefore, two low-complexity high-performance algorithms are proposed. The first algorithm is based on a fast non-dominated ranking genetic algorithm with an elite, which is able to explore the Pareto bound of the considered problem. The second algorithm is based on a reinforcement learning framework, which is able to maximize the weighted sum of employer net profit and employee satisfaction. Numerical results show that the number of tasks assigned to employees affects both employee satisfaction and employer net profit. The Pareto bounds and Pareto optimal solutions based on the solutions of the two proposed algorithms are also presented numerically, which quantitatively characterize the tradeoff between employer net profit and employee satisfaction.","PeriodicalId":258223,"journal":{"name":"Journal of Systems Science and Information","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449938","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}
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