Ho-Keun Yi, T. Qu, Kai Zhang, Mingxing Li, G. Huang, Zefeng Chen
At present, the development of the global manufacturing industry is still in the transition stage from Industry 3.0 to Industry 4.0 (i.e., Industry 3.X), and the production logistics system is becoming more and more complex due to the individualization of customer demands and the high frequency of order changes. In order to systematically analyze the research status and dynamic evolution trend of production logistics in the Industry 3.X stage, this paper designed a Log-Likelihood ratio-based latent Dirichlet allocation (LLR-LDA) algorithm based on bibliometrics and knowledge graph technology, taking the literature of China National Knowledge Infrastructure and Web of Science database as the data source. In-depth bibliometric analysis of literature was carried out from research progress, hotspot evolution, and frontier trends. At the same time, taking the case of scientific research projects overcome by our research group as an example, it briefly introduced the synchronized decision-making framework of digital twin-enabled production logistics system. It is expected to broaden the research boundary of production logistics in the Industry 3.X stage, promote the development and progress of the industry, and provide valuable reference for steadily moving towards the Industry 4.0 stage.
目前，全球制造业的发展仍处于从工业3.0到工业4.0(即工业3.X)的过渡阶段，由于客户需求的个性化和订单变化的高频率，生产物流系统变得越来越复杂。为了系统地分析工业生产物流的研究现状和动态演变趋势。X阶段，以中国国家知识基础设施和Web of Science数据库的文献为数据源，基于文献计量学和知识图谱技术，设计了一种基于对数似然比的潜在狄利克雷分配(LLR-LDA)算法。从研究进展、热点演变、前沿趋势等方面对文献计量学进行了深入分析。同时，以课题组攻克的科研项目为例，简要介绍了数字化双支持生产物流系统的同步决策框架。它有望拓宽工业生产物流的研究边界。X阶段，促进行业的发展进步，为稳步迈向工业4.0阶段提供有价值的参考。
{"title":"Production Logistics in Industry 3.X: Bibliometric Analysis, Frontier Case Study, and Future Directions","authors":"Ho-Keun Yi, T. Qu, Kai Zhang, Mingxing Li, G. Huang, Zefeng Chen","doi":"10.3390/systems11070371","DOIUrl":"https://doi.org/10.3390/systems11070371","url":null,"abstract":"At present, the development of the global manufacturing industry is still in the transition stage from Industry 3.0 to Industry 4.0 (i.e., Industry 3.X), and the production logistics system is becoming more and more complex due to the individualization of customer demands and the high frequency of order changes. In order to systematically analyze the research status and dynamic evolution trend of production logistics in the Industry 3.X stage, this paper designed a Log-Likelihood ratio-based latent Dirichlet allocation (LLR-LDA) algorithm based on bibliometrics and knowledge graph technology, taking the literature of China National Knowledge Infrastructure and Web of Science database as the data source. In-depth bibliometric analysis of literature was carried out from research progress, hotspot evolution, and frontier trends. At the same time, taking the case of scientific research projects overcome by our research group as an example, it briefly introduced the synchronized decision-making framework of digital twin-enabled production logistics system. It is expected to broaden the research boundary of production logistics in the Industry 3.X stage, promote the development and progress of the industry, and provide valuable reference for steadily moving towards the Industry 4.0 stage.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77147114","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}
Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. The importance of considering location planning of BRT stops when optimizing the offset is thereby verified.
{"title":"Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops","authors":"Wei Wu, Xiao-long Luo, Baiying Shi","doi":"10.3390/systems11070366","DOIUrl":"https://doi.org/10.3390/systems11070366","url":null,"abstract":"Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. The importance of considering location planning of BRT stops when optimizing the offset is thereby verified.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85084113","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}
Systems precision medicine is an interdisciplinary approach that recognises the complexity of diseases and emphasises the integration of clinical knowledge, multi-omics data, analytical models, and the expertise of physicians and data analysts to personalise the care pathway in complex diseases, such as cancer or diabetes. The aim is to gain a comprehensive understanding of diseases by analysing individual components and identifying relevant aspects for therapy and diagnosis. Key components, their interactions and emerging patterns can be studied using statistical, mathematical and computational tools. The combination of data analysis and clinical evaluation is crucial to effective decision-making, emphasising the need for an integrative approach rather than relying on data alone. Therefore, the crucial point discussed in this paper is that the “computational” part and the “artistic” part (i.e., the physician’s intuition) cannot be separated, and therefore, systems precision medicine can be configured as a collective work of art, involving not only different medical professionals but also, and above all, professional data analysts. The work is “artistic” because data and mathematics alone, without medical knowledge of the context, are not enough. But the work is also “collective” in the sense that it must be the place of cultural integration between the professional intuition of the physician, which cannot be translated into mathematical formulas, and the ability to extract information from multi-omics data of the data analysts, who instead use formal and computational mathematical methods. However, to drive the medical revolution and reassemble a patient’s parts, data analysts need to be involved in the hospital context, and precision medicine physicians should embrace data analytical perspectives. This will require ongoing dialogue, new languages of communication, and education that promotes continuous learning and collaboration between professions, fostering a new level of interdisciplinary collaboration for personalised care.
{"title":"Systems Precision Medicine: Putting the Pieces Back Together","authors":"L. Farina","doi":"10.3390/systems11070367","DOIUrl":"https://doi.org/10.3390/systems11070367","url":null,"abstract":"Systems precision medicine is an interdisciplinary approach that recognises the complexity of diseases and emphasises the integration of clinical knowledge, multi-omics data, analytical models, and the expertise of physicians and data analysts to personalise the care pathway in complex diseases, such as cancer or diabetes. The aim is to gain a comprehensive understanding of diseases by analysing individual components and identifying relevant aspects for therapy and diagnosis. Key components, their interactions and emerging patterns can be studied using statistical, mathematical and computational tools. The combination of data analysis and clinical evaluation is crucial to effective decision-making, emphasising the need for an integrative approach rather than relying on data alone. Therefore, the crucial point discussed in this paper is that the “computational” part and the “artistic” part (i.e., the physician’s intuition) cannot be separated, and therefore, systems precision medicine can be configured as a collective work of art, involving not only different medical professionals but also, and above all, professional data analysts. The work is “artistic” because data and mathematics alone, without medical knowledge of the context, are not enough. But the work is also “collective” in the sense that it must be the place of cultural integration between the professional intuition of the physician, which cannot be translated into mathematical formulas, and the ability to extract information from multi-omics data of the data analysts, who instead use formal and computational mathematical methods. However, to drive the medical revolution and reassemble a patient’s parts, data analysts need to be involved in the hospital context, and precision medicine physicians should embrace data analytical perspectives. This will require ongoing dialogue, new languages of communication, and education that promotes continuous learning and collaboration between professions, fostering a new level of interdisciplinary collaboration for personalised care.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81143967","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}
WooChul Choi, Taehoon Kim, JoonYeop Na, Junhee Youn
Recently, the demand for citizen-sensible service solutions such as traffic, crime prevention, and disasters in smart cities is increasing. In order to provide technology-based smart city services, local government control centers could be utilized. Accordingly, this paper presented a method for selecting a control center-based dynamic object information utilization service model through in-depth interviews with 26 related local government control center operation personnel. A comparative analysis according to the size of the local government to which the evaluator belongs was also performed. As a methodology, Fuzzy AHP was used, which can support rational decision-making by mathematically expressing ambiguous phenomena such as subjective and uncertain judgments. The summary of the research results is as follows. Services related to recent incidents in South Korea (e.g., school zone traffic accidents and lowland inundation) were identified as very important. These social issues are significant factors in policy decisions. In comparing the results for each urban scale, the importance of pedestrian safety services on backside roads and main road traffic services was found to be important in the metropolitan area and regional, medium, and small cities, respectively. This was attributed to metropolitan cities with high population density, and medium and small cities experiencing alienated traffic information. In metropolitan areas, new services are highly important owing to the demand for a more scientific control service and future mobility based on a sound control infrastructure. In medium and small cities, facility management services were assessed relatively highly owing to the poor conditions of regional cities with a lack of supervising personnel in the field and a lack of surveillance system infrastructure. This paper was able to confirm the difference in service preference by city size, and it is necessary to select the optimal service model considering these results.
{"title":"Assessment of Dynamic Object Information Utilization Service in a Control Center for Each Urban Scale via Fuzzy AHP","authors":"WooChul Choi, Taehoon Kim, JoonYeop Na, Junhee Youn","doi":"10.3390/systems11070368","DOIUrl":"https://doi.org/10.3390/systems11070368","url":null,"abstract":"Recently, the demand for citizen-sensible service solutions such as traffic, crime prevention, and disasters in smart cities is increasing. In order to provide technology-based smart city services, local government control centers could be utilized. Accordingly, this paper presented a method for selecting a control center-based dynamic object information utilization service model through in-depth interviews with 26 related local government control center operation personnel. A comparative analysis according to the size of the local government to which the evaluator belongs was also performed. As a methodology, Fuzzy AHP was used, which can support rational decision-making by mathematically expressing ambiguous phenomena such as subjective and uncertain judgments. The summary of the research results is as follows. Services related to recent incidents in South Korea (e.g., school zone traffic accidents and lowland inundation) were identified as very important. These social issues are significant factors in policy decisions. In comparing the results for each urban scale, the importance of pedestrian safety services on backside roads and main road traffic services was found to be important in the metropolitan area and regional, medium, and small cities, respectively. This was attributed to metropolitan cities with high population density, and medium and small cities experiencing alienated traffic information. In metropolitan areas, new services are highly important owing to the demand for a more scientific control service and future mobility based on a sound control infrastructure. In medium and small cities, facility management services were assessed relatively highly owing to the poor conditions of regional cities with a lack of supervising personnel in the field and a lack of surveillance system infrastructure. This paper was able to confirm the difference in service preference by city size, and it is necessary to select the optimal service model considering these results.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87930953","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}
The new retail focuses on the high integration between online and offline channels. The main problems faced by the development of the new retail are the interest balance of all decision subjects, the pricing strategy, and the coordination of online and offline channels. This paper considers the effect of the new retail firms’ delivery time and establishes a two-part tariff contract to study the decision-making and coordination of the new retail fresh products supply chain. This paper constructs cooperative and non-cooperative models and employs the cooperative model as the benchmark case to realize the coordination. It is found that when the delivery time has little effect on the market demand, the offline store often should pay more fixed charges to the new retail firm. With the increased impact of delivery time on market demand, the fixed charges paid by the offline store become smaller. Under the coordination decision model, the offline store pays fixed charges to compensate for the new retail firm’s early delivery costs, but its interests still increase compared with the decentralized decision model. This study models the time-dependent demand for fresh products and proposes an incentive mechanism to coordinate the new retail fresh products’ supply chain; further, it demonstrates that the prices can be significantly decreased with the designed contract, and all the supply chain members can benefit from Pareto improvement.
{"title":"Research on Incentive and Coordination Strategy of Fresh Products' Supply Chain with Delivery Time under New Retail","authors":"Shuiwang Zhang, Qianlan Ding","doi":"10.3390/systems11070365","DOIUrl":"https://doi.org/10.3390/systems11070365","url":null,"abstract":"The new retail focuses on the high integration between online and offline channels. The main problems faced by the development of the new retail are the interest balance of all decision subjects, the pricing strategy, and the coordination of online and offline channels. This paper considers the effect of the new retail firms’ delivery time and establishes a two-part tariff contract to study the decision-making and coordination of the new retail fresh products supply chain. This paper constructs cooperative and non-cooperative models and employs the cooperative model as the benchmark case to realize the coordination. It is found that when the delivery time has little effect on the market demand, the offline store often should pay more fixed charges to the new retail firm. With the increased impact of delivery time on market demand, the fixed charges paid by the offline store become smaller. Under the coordination decision model, the offline store pays fixed charges to compensate for the new retail firm’s early delivery costs, but its interests still increase compared with the decentralized decision model. This study models the time-dependent demand for fresh products and proposes an incentive mechanism to coordinate the new retail fresh products’ supply chain; further, it demonstrates that the prices can be significantly decreased with the designed contract, and all the supply chain members can benefit from Pareto improvement.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79332577","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}
Data trading is important for optimizing the allocation of data elements. However, data can be easily copied, disseminated, or resold, leading to disorderly development in the data trading market, and raising the issue of data governance. Data trading involves various participants, while existing research lacks an understanding of participant interactions and strategy adoption, as well as determination of optimal strategies for the participants. To address these gaps and provide insights for the governance of data trading platforms, this paper proposes an evolutionary game model for the governance of data trading involving three parties: data suppliers, demanders, and trading platforms. Our findings reveal that data trading platforms choosing to govern, data suppliers choosing to innovate positively, and data demanders choosing not to resell can be achieved under certain conditions. We also find that an increase in the price of data trading or the number of transactions can weaken the effectiveness of platform governance and make data trading more difficult to govern. Additionally, the incentives for data innovation provided by the trading platform can significantly promote data suppliers to innovate data positively. However, when these incentives are too high, the platform may weaken its level of governance or even move towards non-governance. Increasing penalties for data resale weakens data demanders’ motivation to resell data, and a higher probability of data resale being reported lowers their motivation to do so. By examining the role of different participants in data trading, the model proposes ways to improve the efficiency and robustness of the data market while better protecting the interests of data traders.
{"title":"Evolutionary Game Analysis of Data Resale Governance in Data Trading","authors":"Yong Sun, Yafeng Zhang, Jinxiao Li, Sihui Zhang","doi":"10.3390/systems11070363","DOIUrl":"https://doi.org/10.3390/systems11070363","url":null,"abstract":"Data trading is important for optimizing the allocation of data elements. However, data can be easily copied, disseminated, or resold, leading to disorderly development in the data trading market, and raising the issue of data governance. Data trading involves various participants, while existing research lacks an understanding of participant interactions and strategy adoption, as well as determination of optimal strategies for the participants. To address these gaps and provide insights for the governance of data trading platforms, this paper proposes an evolutionary game model for the governance of data trading involving three parties: data suppliers, demanders, and trading platforms. Our findings reveal that data trading platforms choosing to govern, data suppliers choosing to innovate positively, and data demanders choosing not to resell can be achieved under certain conditions. We also find that an increase in the price of data trading or the number of transactions can weaken the effectiveness of platform governance and make data trading more difficult to govern. Additionally, the incentives for data innovation provided by the trading platform can significantly promote data suppliers to innovate data positively. However, when these incentives are too high, the platform may weaken its level of governance or even move towards non-governance. Increasing penalties for data resale weakens data demanders’ motivation to resell data, and a higher probability of data resale being reported lowers their motivation to do so. By examining the role of different participants in data trading, the model proposes ways to improve the efficiency and robustness of the data market while better protecting the interests of data traders.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85406174","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}
Yuan Tian, Jenny Basran, J. Stempien, Adrienne Danyliw, Graham Fast, Patrick Falastein, N. Osgood
We detail a case study using a participatory modeling approach in the development and use of discrete-event simulations to identify intervention strategies aimed at reducing emergency department (ED) wait times in a Canadian health policy setting. A four-stage participatory modeling approach specifically adapted to the local policy environment was developed to engage stakeholders throughout the modeling processes. The participatory approach enabled a provincial team to engage a broad range of stakeholders to examine and identify the causes and solutions to lengthy ED wait times in the studied hospitals from a whole-system perspective. Each stage of the approach was demonstrated through its application in the case study. A novel and key feature of the participatory modeling approach was the development and use of a multi-criteria framework to identify and prioritize interventions to reduce ED wait times. We conclude with a discussion on lessons learned, which provide insights into future development and applications of participatory modeling methods to facilitate policy development and build multi-stakeholder consensus.
{"title":"Participatory Modeling with Discrete-Event Simulation: A Hybrid Approach to Inform Policy Development to Reduce Emergency Department Wait Times","authors":"Yuan Tian, Jenny Basran, J. Stempien, Adrienne Danyliw, Graham Fast, Patrick Falastein, N. Osgood","doi":"10.3390/systems11070362","DOIUrl":"https://doi.org/10.3390/systems11070362","url":null,"abstract":"We detail a case study using a participatory modeling approach in the development and use of discrete-event simulations to identify intervention strategies aimed at reducing emergency department (ED) wait times in a Canadian health policy setting. A four-stage participatory modeling approach specifically adapted to the local policy environment was developed to engage stakeholders throughout the modeling processes. The participatory approach enabled a provincial team to engage a broad range of stakeholders to examine and identify the causes and solutions to lengthy ED wait times in the studied hospitals from a whole-system perspective. Each stage of the approach was demonstrated through its application in the case study. A novel and key feature of the participatory modeling approach was the development and use of a multi-criteria framework to identify and prioritize interventions to reduce ED wait times. We conclude with a discussion on lessons learned, which provide insights into future development and applications of participatory modeling methods to facilitate policy development and build multi-stakeholder consensus.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83993474","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}
Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback systems or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES = 0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback systems.
{"title":"Designing Effective Instructional Feedback Using a Diagnostic and Visualization System: Evidence from a High School Biology Class","authors":"Lin Ma, Xuedi Zhang, Zhifeng Wang, Heng Luo","doi":"10.3390/systems11070364","DOIUrl":"https://doi.org/10.3390/systems11070364","url":null,"abstract":"Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback systems or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES = 0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback systems.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88121553","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}
This paper develops a new unified theoretical general equilibrium model in which the interactions between heterogeneous workers and firms influence heterogeneous city evolutions. Given the heterogeneous worker–firm–city framework, I study in depth the possible heterogenous city evolutions and the resulting implications on the labor market, as well as on overall productivity. In particular, it is shown that the same exogenous shocks may lead to completely different results depending on the relative dominance of the two countervailing effects of congestion and agglomeration. In an open economy setting, it is also shown that such relative dominance may affect the trading partner and generate the comovement of city evolution in each country.
{"title":"A Theory of Heterogeneous City Evolution with Heterogenous Agents","authors":"Jaewon Jung","doi":"10.3390/systems11070360","DOIUrl":"https://doi.org/10.3390/systems11070360","url":null,"abstract":"This paper develops a new unified theoretical general equilibrium model in which the interactions between heterogeneous workers and firms influence heterogeneous city evolutions. Given the heterogeneous worker–firm–city framework, I study in depth the possible heterogenous city evolutions and the resulting implications on the labor market, as well as on overall productivity. In particular, it is shown that the same exogenous shocks may lead to completely different results depending on the relative dominance of the two countervailing effects of congestion and agglomeration. In an open economy setting, it is also shown that such relative dominance may affect the trading partner and generate the comovement of city evolution in each country.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80986029","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}
Haiyan Yan, Linlin Wang, J. Goh, Wuzhi Shen, John Richardson, Xinyue Yan
Given the growing importance of system dynamics (SD) in solving increasingly complex and dynamic problems in any country, we believe SD education will become an imperative leverage point in helping us deal with our uncertain future. This study tries to understand the causal relationships in proliferating SD education by a system dynamics group modelling approach in China. Based on a questionnaire survey and a group model building (GMB) workshop, we aim to explore the interactions of feedback loops in the constructed causal loop diagram (CLD). This uncovers insights into what constitutes the growth of SD education in China and helps to guide the design and implementation of policies to achieve this growth. We conclude that it is important and relevant to find ways to improve, including the construction of an SD teaching platform to integrate normative resources, providing opportunities for teacher training, enhancing the availability and accessibility of SD education, and building networks with international partners. The results of our study may set the foundation for further research to extend the generalizability of our insights and methodological approaches to other countries.
{"title":"Towards Understanding the Causal Relationships in Proliferating SD Education - A System Dynamics Group Modelling Approach in China","authors":"Haiyan Yan, Linlin Wang, J. Goh, Wuzhi Shen, John Richardson, Xinyue Yan","doi":"10.3390/systems11070361","DOIUrl":"https://doi.org/10.3390/systems11070361","url":null,"abstract":"Given the growing importance of system dynamics (SD) in solving increasingly complex and dynamic problems in any country, we believe SD education will become an imperative leverage point in helping us deal with our uncertain future. This study tries to understand the causal relationships in proliferating SD education by a system dynamics group modelling approach in China. Based on a questionnaire survey and a group model building (GMB) workshop, we aim to explore the interactions of feedback loops in the constructed causal loop diagram (CLD). This uncovers insights into what constitutes the growth of SD education in China and helps to guide the design and implementation of policies to achieve this growth. We conclude that it is important and relevant to find ways to improve, including the construction of an SD teaching platform to integrate normative resources, providing opportunities for teacher training, enhancing the availability and accessibility of SD education, and building networks with international partners. The results of our study may set the foundation for further research to extend the generalizability of our insights and methodological approaches to other countries.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87414596","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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