已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Do Investors Rely on Robots? Evidence from an Experimental Study

机器人 业务 计算机科学 计量经济学 经济 人工智能
作者
Barbara Alemanni,Andrej Angelovski,Daniela Di Cagno,Arianna Galliera,Nadia Linciano,Francesca Marazzi,Paola Soccorso
出处
期刊:Social Science Research Network [Social Science Electronic Publishing]
被引量:5
标识
DOI:10.2139/ssrn.3697232
摘要

Robo advice has moved its first steps in the Anglo-Saxon countries and is now rapidly gaining market share at a global level. The phenomenon fueled a growing and still not conclusive institutional debate about potential benefits and risks to financial consumers, based also on investors’ biases and behaviours that online platforms could trigger to the detriment of robo advisees. The present paper provides some insights into attitudes and behaviours that might prevail in a digital environment among young investors, representing the category of users potentially more involved by the development of the automated advice. In detail, the study investigates whether individuals’ propensity to follow the recommendation received from an advisor changes depending on whether the advisor is a human or a robot. The analysis is based on data collected through an ad hoc developed laboratory experiment run in the Cesare Lab of LUISS University with a sample of 180 students. Students were given an initial monetary endowment and were asked to choose between six different portfolios of financial activities; after being profiled through a questionnaire aimed at eliciting their risk tolerance (Grable and Lytton’s Risk Tolerance Quiz; 2003), they received the advice, either from a human advisor or from a robo advisor (i.e. via a computer platform) depending on the treatment they had randomly assigned before entering the experimental session. Then, they were asked again to choose among the six portfolios in order to capture whether the propensity to follow the recommendation depends on its source (human versus robo). Finally, participants were asked to answer several questions eliciting risk preferences, financial literacy (actual and perceived) and digital literacy, serving as control variables when modelling the probability to follow the advice.Our results show that the probability to follow the advice does not depend on the source of the recommendation but rather on the alignment between the self-directed choice made before receiving the advice and the recommendation subsequently received: the propensity to follow the advisor (either human or robo) increases if the advice confirms individual’s own beliefs about her/his investor profile. This result might be explained by referring to individuals’ attitude towards the so called ‘confirmation bias’. However, when the self-directed choice differs from the recommendation received, participants may be more likely to follow the advice given by a human advisor and less likely to follow the advice formulated by an algorithm. Also the gender of the advisor seems to matter: women tend to follow the advice provided by a female advisor more frequently compared to the case of the recommendation given by a male advisor. This work is part of a wider research on FinTech that CONSOB started in 2016, in collaboration with several Italian universities, with the aim of exploring opportunities and risks for investor protection and the financial system as a whole, related to the application of technological innovation to the provision of financial services. In particular, supplementing Lener, Linciano and Soccorso (2019, edited by) and Caratelli et al. (2019), this document widens the field of investigation by referring to a specific target of the population - the so called millennials and post-millennials – and using complementary and innovative methods. According to an evidence-based approach, insights from the present study may suggest specific investor protection initiatives, also in terms of financial education activities designed for a clearly-identified segment of the population (the so called millennials and post-millennials, in this case).Evidence from the present work might be extended further with respect to the consumers’ perception of the fairness of algorithms used to provide financial services, the cognitive heuristics and biases underlying decision making process and investments in the digital environment and nudges which may be used to enhance investor protection.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
李伟峰完成签到,获得积分10
刚刚
刚刚
刚刚
imkhun1021发布了新的文献求助10
2秒前
3秒前
yuanyuan发布了新的文献求助10
5秒前
6秒前
皆可发布了新的文献求助10
6秒前
imkhun1021完成签到,获得积分10
6秒前
7秒前
XudongHou发布了新的文献求助10
8秒前
wen完成签到,获得积分10
10秒前
12秒前
12秒前
桐桐应助123456采纳,获得10
12秒前
12秒前
Orange应助俏皮元珊采纳,获得10
13秒前
BEI发布了新的文献求助10
14秒前
14秒前
15秒前
15秒前
15秒前
FashionBoy应助满意妙梦采纳,获得10
15秒前
走走发布了新的文献求助10
16秒前
lobule发布了新的文献求助10
16秒前
17秒前
17秒前
Why发布了新的文献求助10
18秒前
18秒前
19秒前
19秒前
小二郎应助阳光的忆文采纳,获得10
20秒前
20秒前
21秒前
李爱国应助皆可采纳,获得10
21秒前
青柠发布了新的文献求助10
22秒前
123456发布了新的文献求助10
22秒前
22秒前
23秒前
仁爱羊发布了新的文献求助30
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Mechanics of Solids with Applications to Thin Bodies 5000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
人脑智能与人工智能 1000
King Tyrant 720
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5599516
求助须知:如何正确求助?哪些是违规求助? 4685187
关于积分的说明 14838060
捐赠科研通 4668727
什么是DOI,文献DOI怎么找? 2538015
邀请新用户注册赠送积分活动 1505447
关于科研通互助平台的介绍 1470804