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Human–machine trans roles conflict in the organization: How sensitive are customers to intelligent robots replacing the human workforce?

代表 劳动力 构造(python库) 任务(项目管理) 知识管理 认知 比例(比率) 授权 数字化转型 计算机科学 业务 心理学 营销 管理 经济 物理 量子力学 神经科学 程序设计语言 经济增长 万维网
作者
Artur Modliński,Paweł Fortuna,Bohdan Rożnowski
出处
期刊:International Journal of Consumer Studies [Wiley]
卷期号:47 (1): 100-117 被引量:26
标识
DOI:10.1111/ijcs.12811
摘要

Abstract In organizations facing digital transformation, intelligent technologies are starting to replace the human workforce. At present, managers delegate tasks to an artificial agent and rarely consider the customer reception of such decisions. This arouses tensions between the main stakeholders of the organization. This paper shows that the rash adaptation of the digital workforce may be perceived as an irresponsible innovation that brings negative consequences for companies. If a task is regarded by customers as dedicated to humans, and managers delegate it to machines, a new type of conflict – human‐machine trans roles conflict (HMTRC), appears. This paper intends to show that customers are sensitive to HMTRC. This research uses quantitative methods and consists of three stages. First, people were asked to indicate which tasks in an organization should be performed by (a) humans and (b) machines. According to these results, two leaflets for customers were designed (low vs. high HMTRC). In the second stage, standard procedures were used to construct a scale measuring customer reactions to HMTRC on three dimensions: cognitive, emotional and behavioural. Ultimately, the scale and two leaflets were used to check how customers react to different intensities of HMTRC. The research results show that customers are aware when HMTRC occurs and perceive it negatively (cognitive response). Moreover, it evokes negative emotions (emotional response) and prompts customers to take action against the company in which this conflict takes place (behavioural response). The practical contribution of this research is the three‐dimensional scale. It may predict customers' reactions to task delegation with different intensities of HMTRC and help build a technologically sustainable organization.
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