Aligning Chatbot Features with Industry Needs: A Comparative Study of User Expectations in Utilitarian and Hedonic Sectors for SMEs

This study explores the optimal chatbot orientation—socially oriented (SO) or task-oriented (TO)—for small and medium-sized enterprises (SMEs) in hedonic versus utilitarian industries. Through a mixed-methods approach combining quantitative data from 166 participants and qualitative interviews, it examines user preferences for chatbot interaction styles, focusing on perceived ease of use (PEOU) and usage intention (UI). Findings highlight a strong preference for SO chatbots in hedonic contexts, emphasizing engaging, human-like interactions, while utilitarian industries showed no significant preference, with efficiency taking precedence. Correlation analysis revealed a robust link between perceived ease of use and usage intention for SO chatbots, underscoring their potential to enhance user engagement. The research provides actionable insights for SMEs to tailor chatbot designs to industry-specific customer expectations, aligning digital tools with business goals and customer satisfaction.

Authors

Publication Details

Published
2025-06-09
DOI
https://doi.org/10.18690/um.fov.4.2025.7
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Aligning Chatbot Features with Industry Needs: A Comparative Study of User Expectations in Utilitarian and Hedonic Sectors for SMEs

Margot M. E. Neggers, Alinda Kokkinou, Denys Bespalko, Jason van Hamond
AI in Service Interactions
article

Aligning Chatbot Features with Industry Needs: A Comparative Study of User Expectations in Utilitarian and Hedonic Sectors for SMEs

Margot M. E. Neggers, Alinda Kokkinou, Denys Bespalko, Jason van Hamond
article en

Abstract

This study explores the optimal chatbot orientation—socially oriented (SO) or task-oriented (TO)—for small and medium-sized enterprises (SMEs) in hedonic versus utilitarian industries. Through a mixed-methods approach combining quantitative data from 166 participants and qualitative interviews, it examines user preferences for chatbot interaction styles, focusing on perceived ease of use (PEOU) and usage intention (UI). Findings highlight a strong preference for SO chatbots in hedonic contexts, emphasizing engaging, human-like interactions, while utilitarian industries showed no significant preference, with efficiency taking precedence. Correlation analysis revealed a robust link between perceived ease of use and usage intention for SO chatbots, underscoring their potential to enhance user engagement. The research provides actionable insights for SMEs to tailor chatbot designs to industry-specific customer expectations, aligning digital tools with business goals and customer satisfaction.

Openalex Percentile: Top 94%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.