A service failure assessment model for smart product consumption experience based on customer perception

Area of Science:

• Human-Computer Interaction
• Service Quality Management
• Consumer Behavior Analysis

Background:

• Customer perception is crucial for evaluating human-computer interaction (HCI) service quality.
• Understanding consumer satisfaction drives sustainable user experiences and marketing strategies.
• Effective product service failure prevention requires analyzing customer perception and satisfaction.

Purpose of the Study:

• To propose a novel service failure evaluation model for HCI.
• To introduce the concept of the 'tolerance area' for evaluating consumer experiences.
• To accurately evaluate and rank potential service failure factors in smart speakers.

Main Methods:

• Developed a hybrid evaluation model combining fuzzy Failure Mode and Effect Analysis (FMEA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS).
• Integrated the 'tolerance area' concept to assess consumer behavioral experiences from purchase to product use.
• Applied the model to identify and prioritize critical service failure factors in smart speakers.

Main Results:

• Identified voice misinterpretation and signal connectivity issues as primary risk factors affecting smart speaker HCI quality.
• Successfully evaluated and ranked potential service failure factors within the defined tolerance area.
• Demonstrated the model's capability to enhance the evaluation of smart speaker HCI service quality.

Conclusions:

• The proposed model accurately identifies and prioritizes critical failure modes in smart speaker services.
• Service failure prevention strategies derived from this model can reduce consumer dissatisfaction.
• Findings offer innovative references for smart product design, marketing, and enhancing overall HCI service quality.