Short answer

When designing customer service systems that incorporate robots, anticipate that customers will hold the company more responsible for robot failures than for human employee failures, and frame robot capabilities to emphasize learning and adaptability.

Field: Innovation & Markets
Source: Journal of service management (2020)
Method: Experimental vignette studies
Evidence: Strong effect

Customers are more likely to hold human employees accountable for service failures than service robots, viewing robot performance as less stable and less indicative of the company's overall capability. This innovation & markets research insight is drawn from a 2020 study published in Journal of service management. Using Experimental vignette studies, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing customer service systems that incorporate robots, anticipate that customers will hold the company more responsible for robot failures than for human employee failures, and frame robot capabilities to emphasize learning and adaptability.

Study

Innovation & MarketsHigh ImpactStrong effect

Customers Attribute Service Failures More to Humans Than Robots, Affecting Brand Perception

Journal of service management · 2020

Key Findings

01Customers attribute greater responsibility for service performance to human employees than to service robots, particularly in cases of service failure.
02The perceived stability of performance is higher for robots than for human employees, suggesting customers expect human improvement but not robot improvement after a failure.
03Robots are perceived as more representative of the firm than individual employees.

Application

Design takeaway

How to apply

When introducing service robots, develop clear communication materials that explain the robot's AI and learning capabilities to manage customer expectations and attributions.

Project actions

01Consider how the choice between a human and an automated system might affect user perception of blame and future performance.
02Investigate how to communicate the capabilities of automated systems to influence user attributions positively.

Method & Evidence

AimHow do customers attribute responsibility and stability to human employees versus service robots following service success or failure?

MethodExperimental vignette studies

ProcedureParticipants were presented with scenarios describing hotel reception or restaurant waiter services, where either a human employee or a robot provided the service, and the outcome was either a success or a failure. They then responded to questions about responsibility and stability.

ContextCustomer service interactions in hospitality (hotels and restaurants)

Variables

IV["Service provider type (human employee vs. robot)","Service outcome (success vs. failure)"]

DV["Attribution of responsibility","Perceived stability of performance"]

CV["Service context (hotel reception, restaurant waiter)","Demographics of respondents"]

Strengths & Limitations

Strengths

+Provides empirical evidence in a field dominated by conceptual work.
+Uses controlled experimental vignettes to isolate specific variables.

Limitations

The scenarios used might be too simplistic to reflect real-world service complexity. Cultural differences in attributing responsibility could also be a factor.

Reliability & validity

The use of vignettes and self-report measures may introduce social desirability bias and limit ecological validity. Reliability of the attribution scales would need to be assessed.

Think critically

To what extent does the perceived 'human-likeness' of a robot influence these attribution biases?

Design Principles

"Customer attributions of responsibility and stability vary significantly between human and automated service providers, influencing brand perception."

This research highlights a critical difference in customer perception between human and robotic service providers. Understanding these attribution biases is crucial for businesses integrating robots into their customer-facing operations, as it directly impacts how service failures are perceived and how the brand is ultimately judged.

What This Means for Your Design

People blame people more than robots when things go wrong with a service, and they think robots are less likely to get better over time than people are.

How to use in your project

1.This research can inform the design of user interfaces for automated systems by highlighting the importance of managing user attributions of responsibility and perceived stability.

Add to My Project

Quick Cite

Paragraph starter

Research indicates that customers tend to attribute service failures more directly to human employees than to service robots. Furthermore, customers perceive human performance as more stable and capable of improvement post-failure compared to robots. This suggests that when designing automated service solutions, it is crucial to manage customer attributions by clearly communicating the learning capabilities of the technology to prevent negative brand perceptions.

Source

Journal of service management

Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success

journal · 2020

View source

Questions About This Research

What does the research say about customers attribute service failures more to humans than robots, affecting brand perception?: When designing customer service systems that incorporate robots, anticipate that customers will hold the company more responsible for robot failures than for human employee failures, and frame robot capabilities to emphasize learning and adaptability. Evidence: Journal of service management (2020).
Why does "Customers Attribute Service Failures More to Humans Than Robots, Affecting Brand Perception" matter for design?: This research highlights a critical difference in customer perception between human and robotic service providers. Understanding these attribution biases is crucial for businesses integrating robots into their customer-facing operations, as it directly impacts how service failures are perceived and how the brand is ultimately judged.
How can designers apply this research?: When designing customer service systems that incorporate robots, anticipate that customers will hold the company more responsible for robot failures than for human employee failures, and frame robot capabilities to emphasize learning and adaptability.
What were the main findings?: Customers attribute greater responsibility for service performance to human employees than to service robots, particularly in cases of service failure.. The perceived stability of performance is higher for robots than for human employees, suggesting customers expect human improvement but not robot improvement after a failure.. Robots are perceived as more representative of the firm than individual employees.
What research method was used?: Experimental vignette studies.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2020 journal from Journal of service management.
What should I do differently in my next project?: When introducing service robots, develop clear communication materials that explain the robot's AI and learning capabilities to manage customer expectations and attributions.
What are the limitations?: The study focused on specific service contexts (hotel reception, restaurant waiter) and may not generalize to all service industries. The use of vignettes might not fully capture the complexity of real-world service encounters.