# The temperature of connection: psychological mechanisms and happiness generation in AI-enabled neighborhoods

## TL;DR

This study explores how AI in neighborhoods affects residents' happiness by identifying key service cues and their psychological pathways.

## Contribution

The paper introduces a framework linking AI service cues to well-being through digital attachment and continued use intention.

## Key findings

- Reliability, usefulness, and ease of use are foundational for digital attachment and well-being.
- Service efficiency and aesthetics amplify well-being but are not standalone drivers.
- Well-being emerges from combinations of cues, not single factors.

## Abstract

Artificial intelligence (AI) is rapidly reshaping neighborhood services, yet we still lack a nuanced understanding of which experiential cues matter, how they combine, and why they relate to residents’ well-being. This study addresses that gap by identifying designable service cues and clarifying their socio-psychological pathways to well-being in AI-enabled neighborhoods.

Drawing on the Cognition–Affect–Conation framework and insights from technology acceptance, service quality, and social presence research, we conceptualized five experiential cues: reliability, perceived usefulness, perceived ease of use, service efficiency, and aesthetic perception. We further positioned digital attachment and continued use intention as key socio-psychological linkages to well-being. Empirically, we used a three-wave survey design with four-week lags across four smart-community pilots in Zhejiang, China (matched panel n = 452). An explanation–prediction–necessity strategy was adopted by triangulating PLS-SEM, artificial neural networks (ANN), and necessary condition analysis (NCA).

Findings converged across methods. Instrumental appraisals—especially reliability, perceived usefulness, and perceived ease of use—formed the foundational conditions for digital attachment and continued engagement, which were strongly associated with higher well-being. Service efficiency and aesthetic perception acted mainly as amplifiers rather than stand-alone drivers. NCA results indicated that no single condition reached necessity, suggesting that residents’ well-being emerges from complementary combinations of experiential cues rather than any one dominant factor.

The findings suggest that well-being in AI-enabled neighborhoods is generated through configurational and pathway-based mechanisms rather than isolated service attributes. Practically, neighborhood service design should prioritize baseline thresholds in reliability, usefulness, and ease of use, while treating efficiency and aesthetics as conversion accelerators. Lightweight participation loops at high-social-presence touchpoints may further strengthen attachment, sustained engagement, and downstream well-being outcomes.