{"title":"信用营销中的算法分类:营销如何塑造不平等","authors":"Léna Pellandini-Simányi","doi":"10.1177/14705931231160828","DOIUrl":null,"url":null,"abstract":"<p><p>While critical marketing studies have discussed algorithm-driven marketing's role in governmentality, subjectivity formation and capitalist accumulation, its role in shaping class inequalities is less studied. Drawing on the performativity of marketing, 'classification situations' and critical algorithm studies, this paper uses the case of credit marketing to propose a twofold framework to analyse how algorithmic marketing shapes the cultural and economic inequalities of class. First, algorithms used for categorizing consumers and matching them with marketing messages and products provide access (1) to different symbolic resources and (2) to credit products with different financial consequences to different consumers depending on their categorization, which contribute to the creation of cultural and economic inequalities, respectively. Second, algorithms of financial advice devices overtake parts of consumer choice. Insofar as different financial preferences and rationalities are scripted into the devices for different client groups, these technologies constitute an additional process that affects social divisions.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":" ","pages":"211-232"},"PeriodicalIF":4.7000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11106845/pdf/","citationCount":"0","resultStr":"{\"title\":\"Algorithmic classifications in credit marketing: How marketing shapes inequalities.\",\"authors\":\"Léna Pellandini-Simányi\",\"doi\":\"10.1177/14705931231160828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>While critical marketing studies have discussed algorithm-driven marketing's role in governmentality, subjectivity formation and capitalist accumulation, its role in shaping class inequalities is less studied. Drawing on the performativity of marketing, 'classification situations' and critical algorithm studies, this paper uses the case of credit marketing to propose a twofold framework to analyse how algorithmic marketing shapes the cultural and economic inequalities of class. First, algorithms used for categorizing consumers and matching them with marketing messages and products provide access (1) to different symbolic resources and (2) to credit products with different financial consequences to different consumers depending on their categorization, which contribute to the creation of cultural and economic inequalities, respectively. Second, algorithms of financial advice devices overtake parts of consumer choice. Insofar as different financial preferences and rationalities are scripted into the devices for different client groups, these technologies constitute an additional process that affects social divisions.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\" \",\"pages\":\"211-232\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11106845/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1177/14705931231160828\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/2/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/14705931231160828","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Algorithmic classifications in credit marketing: How marketing shapes inequalities.
While critical marketing studies have discussed algorithm-driven marketing's role in governmentality, subjectivity formation and capitalist accumulation, its role in shaping class inequalities is less studied. Drawing on the performativity of marketing, 'classification situations' and critical algorithm studies, this paper uses the case of credit marketing to propose a twofold framework to analyse how algorithmic marketing shapes the cultural and economic inequalities of class. First, algorithms used for categorizing consumers and matching them with marketing messages and products provide access (1) to different symbolic resources and (2) to credit products with different financial consequences to different consumers depending on their categorization, which contribute to the creation of cultural and economic inequalities, respectively. Second, algorithms of financial advice devices overtake parts of consumer choice. Insofar as different financial preferences and rationalities are scripted into the devices for different client groups, these technologies constitute an additional process that affects social divisions.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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