Study
Innovation & DesignHigh ImpactStrong effect

Personal experience with robots significantly boosts workplace acceptance

Direct, positive interactions with robots, regardless of location, are the strongest predictor of an individual's willingness to accept them in their work environment.

International Journal of Social Robotics · 2019

01

Key Findings

  • 01Individual factors, particularly personal experience with robots, were stronger predictors of robot acceptance than national-level factors.
  • 02Countries with a higher technological orientation showed greater overall acceptance of robots.
  • 03The risk of job automation did not significantly predict robot acceptance at the national level.
02

Application

Design takeaway

Design and deploy robotic systems in ways that allow for direct, positive user engagement to build trust and acceptance.

How to apply

When introducing new robotic systems into a workplace, ensure ample opportunities for employees to interact with the technology in a supportive environment before full deployment.

Project actions

  • 01When researching user attitudes towards a new technology, consider how personal experience might influence their opinions.
  • 02Think about how to design prototypes or demonstrations that allow potential users to interact with your design.
03

Method & Evidence

AimTo investigate the individual and national factors influencing robot acceptance at work within EU countries.
MethodMultilevel analysis
ProcedureThe study analyzed data from Eurobarometer surveys conducted in 2012 and 2014, incorporating country-specific data from the World Bank. A multilevel model was employed to account for both individual-level attributes and national-level factors influencing robot acceptance.
SampleOver 54,000 participants (26,751 in 2012, 27,801 in 2014)
ContextWorkplace automation and human-robot interaction across 27 EU countries.

Variables

IV["Personal experience with robots","Country's technological orientation"]
DVRobot acceptance at work (RAW)
CV["National-level factors (e.g., risk of job automation)","Individual background factors"]
04

Strengths & Limitations

Strengths

  • +Large sample size across multiple countries provides robust statistical power.
  • +Multilevel analysis accounts for complex nested data structures.

Limitations

Self-reported data can be subjective. The study's focus on EU countries may limit generalizability to other cultural contexts.

Reliability & validity

The use of large, established survey datasets (Eurobarometer) enhances reliability. The multilevel modeling approach strengthens the validity by accounting for contextual factors.

Think critically

To what extent can the findings regarding robot acceptance be generalized to other forms of automation or digital technologies?

05

Design Principles

"Facilitate positive user experiences through direct interaction to drive technology adoption."

Understanding the drivers of robot acceptance is crucial for successful integration of automation in the workplace. Designers and engineers can leverage this insight to develop strategies that foster positive user experiences, thereby mitigating resistance and maximizing the benefits of robotic systems.

06

What This Means for Your Design

If people get to try out robots and have a good experience, they are much more likely to accept them at their job.

How to use in your project

  • 1.Reference this study when discussing user attitudes and the importance of user experience in your design process, especially if your project involves automation or new technology.
07

Add to My Project

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Quick Cite

(2019). Robot Acceptance at Work: A Multilevel Analysis Based on 27 EU Countries. International Journal of Social Robotics. https://doi.org/10.1007/s12369-019-00526-x Retrieved from https://designdex.org/study/ea9d0aca-a765-42e9-8bd5-725fa86e29b2/personal-experience-with-robots-significantly-boosts-workplace-acceptance

Paragraph starter

Research indicates that personal experience is a significant driver of acceptance for new technologies in the workplace, with individuals who have interacted positively with robots showing higher levels of acceptance (Turja & Oksanen, 2019). This underscores the importance of designing for positive user engagement and providing opportunities for direct interaction during the implementation of new systems.

09

Source

International Journal of Social Robotics

Robot Acceptance at Work: A Multilevel Analysis Based on 27 EU Countries

journal · 2019

View source

Questions about this research

What does the research say about personal experience with robots significantly boosts workplace acceptance?
Design and deploy robotic systems in ways that allow for direct, positive user engagement to build trust and acceptance. Evidence: International Journal of Social Robotics (2019).
Why does "Personal experience with robots significantly boosts workplace acceptance" matter for design?
Understanding the drivers of robot acceptance is crucial for successful integration of automation in the workplace. Designers and engineers can leverage this insight to develop strategies that foster positive user experiences, thereby mitigating resistance and maximizing the benefits of robotic systems.
How can designers apply this research?
Design and deploy robotic systems in ways that allow for direct, positive user engagement to build trust and acceptance.
What were the main findings?
Individual factors, particularly personal experience with robots, were stronger predictors of robot acceptance than national-level factors.. Countries with a higher technological orientation showed greater overall acceptance of robots.. The risk of job automation did not significantly predict robot acceptance at the national level.
What research method was used?
Multilevel analysis with Over 54,000 participants (26,751 in 2012, 27,801 in 2014).
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2019 journal from International Journal of Social Robotics.
What should I do differently in my next project?
When introducing new robotic systems into a workplace, ensure ample opportunities for employees to interact with the technology in a supportive environment before full deployment.
What are the limitations?
The study relies on self-reported data and may not fully capture nuanced cultural differences or the specific nature of robot-user interactions.
Is there evidence that robot acceptance affects design outcomes?
People are more likely to accept robots at work if they have had positive personal experiences with them. While a country's general openness to technology plays a role, individual encounters are the most influential factor. Understanding the drivers of robot acceptance is crucial for successful integration of automatio Source: International Journal of Social Robotics (2019).
Where does this positive user research apply?
Workplace automation and human-robot interaction across 27 EU countries. It sits within innovation & design research on designdex.org.

Related research topics

robot acceptance design research · evidence on robot acceptance · does robot acceptance improve design outcomes · positive user studies for designers · robot acceptance and positive user findings · innovation & design research evidence