Evidence map›Paper›PMID 41642422›Full record

ArticleCarbon balance and management2026

Shaping consumer behavior with artificial intelligence and brand elements.

Barış Armutcu

Abstract read
In one paragraph

Article in Carbon balance and management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Barış ArmutcuSocial Sciences Institute, Business and Marketing Administration , Igdır University , Iğdır , Türkiye. b.armutcu2765@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study is one of the few contextual and integrative empirical studies examining how artificial intelligence marketing efforts (AI MEs) can shape consumers' green purchasing behavior (GPB), particularly among Generation Z consumers in developing countries, and thus contribute to green consumption and brand element relationships. This study investigates the direct and mediating effects of both AI MEs (information, customisation, interaction, and accessibility) and brand elements (brand preference, brand experience, and brand trust) on consumers' GPBs based on the SOR model. An analysis based on surveys (n = 609; SEM-ANN) revealed that AI MEs significantly affected brand elements and GPB, and that brand experience and brand preference were significant mediators in the relationship between AI MEs and GPB. The study also found a significant relationship between brand elements and GPB in the present study. The ANN analysis showed that the most important variables in explaining GPB were brand preference, AI MEs, and brand experience. By integrating AI marketing and brand elements into the conceptualisation of GPB, this study contextually enriches and integrates the limited body of knowledge on sustainable consumer behaviour. The findings offer new theoretical insights and practical guidance for policymakers and businesses aiming to leverage AI to promote environmentally responsible consumption.

Indexed as

Artificial intelligence (AI)Brand experienceBrand preferenceBrand trustCostumer behaviourGreen consumptionSOR model

Identifiers

PMID41642422
PMCPMC12964972

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.