{"title":"忽略复杂的网络结构低估了大型项目的延迟","authors":"C. Ellinas, D. Avraam, C. Nicolaides","doi":"10.1088/2632-072X/accef0","DOIUrl":null,"url":null,"abstract":"Completing large-scale projects on time is a daunting challenge, partly due to the intricate network of dependencies between a project’s activities. To support this challenge, existing theory focuses on predicting whether a delay in completing a single activity is likely to spread and impact downstream activities. Using fine-grained information from 68 546 activities and 84 934 pairs, associated with the delivery of a $1.86Bn infrastructure project, we show that the core mechanism that underpins existing theory underestimates delay propagation. To elucidate the mechanisms that drive delay, we generated null models that destroyed the structural and temporal correlations of the original project activity network. By doing so, we argue that this underestimation is the result of neglecting endogenous structural features within the project’s activity network. Formulating a new mechanism that utilizes both temporal and structural features may help improve our capacity to predict how delays spread within projects.","PeriodicalId":53211,"journal":{"name":"Journal of Physics Complexity","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neglecting complex network structures underestimates delays in a large-capital project\",\"authors\":\"C. Ellinas, D. Avraam, C. Nicolaides\",\"doi\":\"10.1088/2632-072X/accef0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Completing large-scale projects on time is a daunting challenge, partly due to the intricate network of dependencies between a project’s activities. To support this challenge, existing theory focuses on predicting whether a delay in completing a single activity is likely to spread and impact downstream activities. Using fine-grained information from 68 546 activities and 84 934 pairs, associated with the delivery of a $1.86Bn infrastructure project, we show that the core mechanism that underpins existing theory underestimates delay propagation. To elucidate the mechanisms that drive delay, we generated null models that destroyed the structural and temporal correlations of the original project activity network. By doing so, we argue that this underestimation is the result of neglecting endogenous structural features within the project’s activity network. Formulating a new mechanism that utilizes both temporal and structural features may help improve our capacity to predict how delays spread within projects.\",\"PeriodicalId\":53211,\"journal\":{\"name\":\"Journal of Physics Complexity\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physics Complexity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/2632-072X/accef0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics Complexity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2632-072X/accef0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Neglecting complex network structures underestimates delays in a large-capital project
Completing large-scale projects on time is a daunting challenge, partly due to the intricate network of dependencies between a project’s activities. To support this challenge, existing theory focuses on predicting whether a delay in completing a single activity is likely to spread and impact downstream activities. Using fine-grained information from 68 546 activities and 84 934 pairs, associated with the delivery of a $1.86Bn infrastructure project, we show that the core mechanism that underpins existing theory underestimates delay propagation. To elucidate the mechanisms that drive delay, we generated null models that destroyed the structural and temporal correlations of the original project activity network. By doing so, we argue that this underestimation is the result of neglecting endogenous structural features within the project’s activity network. Formulating a new mechanism that utilizes both temporal and structural features may help improve our capacity to predict how delays spread within projects.