Arianna Costantini, Andrea Scalco, Riccardo Sartori, Elena M Tur, Andrea Ceschi
{"title":"计算亲社会行为的理论。","authors":"Arianna Costantini, Andrea Scalco, Riccardo Sartori, Elena M Tur, Andrea Ceschi","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Most relevant theories of prosocial behavior aim at exploring and understanding helping motivations from an evolutionary perspective. This article summarizes findings from research on prosocial behavior from both a socio-economic and psychological perspective. Building on literature exploring the basic processes and determinant variables of helping, we propose a stochastic and dynamic model to simulate prosocial behaviors over time and recreate evolutionary processes of helping behaviors. Such a mathematical model formalizes a procedure for dynamic simulations, including agent-based modeling, which implies non-linear dynamics of prosocial processes underlying helping motivations. Practical implications for organizations and societies are addressed.</p>","PeriodicalId":46218,"journal":{"name":"Nonlinear Dynamics Psychology and Life Sciences","volume":"23 2","pages":"297-313"},"PeriodicalIF":0.6000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Theories for Computing Prosocial Behavior.\",\"authors\":\"Arianna Costantini, Andrea Scalco, Riccardo Sartori, Elena M Tur, Andrea Ceschi\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Most relevant theories of prosocial behavior aim at exploring and understanding helping motivations from an evolutionary perspective. This article summarizes findings from research on prosocial behavior from both a socio-economic and psychological perspective. Building on literature exploring the basic processes and determinant variables of helping, we propose a stochastic and dynamic model to simulate prosocial behaviors over time and recreate evolutionary processes of helping behaviors. Such a mathematical model formalizes a procedure for dynamic simulations, including agent-based modeling, which implies non-linear dynamics of prosocial processes underlying helping motivations. Practical implications for organizations and societies are addressed.</p>\",\"PeriodicalId\":46218,\"journal\":{\"name\":\"Nonlinear Dynamics Psychology and Life Sciences\",\"volume\":\"23 2\",\"pages\":\"297-313\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nonlinear Dynamics Psychology and Life Sciences\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PSYCHOLOGY, MATHEMATICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nonlinear Dynamics Psychology and Life Sciences","FirstCategoryId":"102","ListUrlMain":"","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PSYCHOLOGY, MATHEMATICAL","Score":null,"Total":0}
Most relevant theories of prosocial behavior aim at exploring and understanding helping motivations from an evolutionary perspective. This article summarizes findings from research on prosocial behavior from both a socio-economic and psychological perspective. Building on literature exploring the basic processes and determinant variables of helping, we propose a stochastic and dynamic model to simulate prosocial behaviors over time and recreate evolutionary processes of helping behaviors. Such a mathematical model formalizes a procedure for dynamic simulations, including agent-based modeling, which implies non-linear dynamics of prosocial processes underlying helping motivations. Practical implications for organizations and societies are addressed.