信用营销中的算法分类:营销如何塑造不平等
1Institute of Marketing and Communication Management, Università Della Svizzera Italiana, Lugano, Switzerland.
概括
算法营销,特别是在信贷方面,通过控制对象征性资源和金融产品的访问,创造了阶级不平等. 它还通过编写的财务建议来塑造消费者选择,加深社会分歧.
科学领域:
- 社会经济学 社会经济学
- 营销科学 营销科学
- 关键算法研究研究 关键算法研究
背景情况:
- 批判性营销研究探讨了算法驱动营销对治理性,主观性和积累的影响.
- 算法营销在加剧阶级不平等方面的作用仍未得到充分研究.
研究的目的:
- 为分析算法营销如何塑造文化和经济阶级不平等提出一个双重框架.
- 调查信用营销的具体情况,以了解这些机制.
主要方法:
- 借鉴营销的执行力",分类情况"和关键算法研究.
- 分析算法如何对消费者进行分类,并影响他们获得资源和金融产品的途径.
主要成果:
- 算法分类影响了获得象征性资源和信贷产品的机会,造成了文化和经济的不平等.
- 财务咨询算法根据客户群体编写消费者选择,进一步影响社会分裂.
结论:
- 算法营销积极促进了基于阶级的文化和经济差异的创造和延续.
- 该研究强调了对营销和金融领域的算法系统进行批判性审查的必要性,以解决社会不平等问题.
相关概念视频
Stereotypes, Prejudice, and Discrimination
90.2K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
90.2K
Stereotype Content Model
14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
In- and Out-Groups
39.0K
People all belong to a gender, race, age, and social economic group. These groups provide a powerful source of our identity and self-esteem (Tajfel & Turner, 1979) and serve as our in-groups. An in-group is a group that we identify with or see ourselves as belonging to.
39.0K
How Data are Classified: Categorical Data
32.5K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
32.5K
Aggregates Classification
317
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
317
Classification of Systems-II
140
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
140


