The AI–consumer–sustainability nexus: a conceptual framework for real estate transformation
Utpal Saikhedkar & Girish Mude
Abstract
Purpose The success in the real estate business depends on the three streams – technology adoption, consumer behaviour and sustainability. While the technology of artificial intelligence (AI) has gained popularity in the marketing of property, the earlier research remains fragmented across the three streams. This paper aims to develop an integrative conceptual model, the AI–consumer–sustainability nexus, to connect these streams in a property–market context. Design/methodology/approach A systematic literature review and thematic synthesis were conducted on 118 Scopus-indexed publications between 2015 and 2025. Themes were coded and consolidated to map pathways and derive hypotheses. To strengthen the conceptual integrity, semi-structured interviews with the stakeholders were conducted (a total of 24 interviews, including 11 with academicians and 13 with practitioners) to assess construct clarity and linkage plausibility. Findings The framework places AI tools in real estate as the main driver and identifies consumer trust, perceived authenticity and value expression as key mediating variables. These variables shape near-term outcomes (purchase intention and market efficiency), which in turn influence longer-term sustainability outcomes. Policy and regulation operate as boundary conditions that can strengthen or weaken the proposed links. A total of 11 hypotheses are presented to guide future empirical testing. Research limitations/implications In this conceptual study, hypotheses are not empirically tested. The review conducted is limited to Scopus literature (2015–2025). The framework guides future operationalisation and testing across housing-market and regulatory settings. Practical implications AI adoption in housing depends on trust, authenticity and value expression, not accuracy alone. Platforms/developers should embed transparency and sustainability cues; regulators can use standards and disclosure to reduce uncertainty and support sustainable outcomes. Originality/value This study provides a housing-specific integrative framework linking AI tools to behavioural and sustainability outcomes, strengthened through stakeholder validation (n = 24) and sets an actionable research agenda.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.