Effects of social proof arguments on collaborative filtering recommender systems

Fábio Roberto Ferreira Borges; Ricardo Teixeira Veiga

doi:10.5585/2025.28214

Autores

Fábio Roberto Ferreira Borges Universidade Federal de Minas Gerais (UFMG), Departamento de Ciências Administrativas (DCAD), Faculdade de Ciências Econômicas (FACE), Belo Horizonte, MG, Brasil https://orcid.org/0000-0003-2588-4730
Ricardo Teixeira Veiga Universidade Federal de Minas Gerais (UFMG), Departamento de Ciências Administrativas (DCAD), Centro de Pós-Graduação e Pesquisas em Administração (CEPEAD), Faculdade de Ciências Econômicas (FACE), Belo Horizonte, MG, Brasil https://orcid.org/0000-0001-5467-0972

DOI:

https://doi.org/10.5585/2025.28214

Palavras-chave:

recommender systems, collaborative filtering, social proof, e-commerce

Resumo

Objective: Social influence in e-commerce environment has taken a key role in the purchasing process, through customer reviews, aggregate ratings, social presence, and other elements. E-commerce companies make extensive use of Recommender Systems, which identify the user’s community behavior patterns to extract useful information and transform it into recommendations. This study aims to analyze the effects of behavioral similarity-based recommendations (e.g. most people who liked movie A also liked movie B, so A and B movies are very similar in users’ taste) (high and low levels) and social proof arguments (absent and present) on recommendation evaluation and purchase intention. Additionally, it investigates whether social proof moderates the impact of similarity-based recommendations in e-commerce environments.

Methodology/Approach: A series of three experiments was conducted using a 2 x 2 factorial design, manipulating behavioral similarity and social proof as independent variables. The dependent variables included recommendation evaluation and purchase intention. The sample sizes for the experiments were 128, 120, and 136 participants, respectively.

Main Results: The findings confirmed the interaction effects of the manipulated factors on the dependent variables in the first two studies. Study 1 tested the social proof argument effect, varying its presence and its absence, with a high and low similarity-based recommendation, as well as its effects on purchase intention and recommendation evaluation. Study 1 results showed significant interactions for Recommendation Evaluation and Purchase Intention. Study 2 was a variation of Study 1 where the environment was changed from using an email marketing piece to a screen of a mobile device. Study 2 also found significant effects on Recommendation Evaluation and Purchase Intention. However, in Study 3, where social proof was represented by an external validation source (IMDb rating), no interaction effects were observed on Recommendation Evaluation and Purchase Intention.

Theoretical/Methodological Contributions: This study makes a significant contribution to the literature by demonstrating that social proof moderates the effects of similarity-based recommendations with its influence varying depending on the type of social proof employed. It highlights the complex role of external validation in shaping consumer perceptions of recommendation systems.

Originality/Relevance: The research addresses a theoretical gap in understanding how social influence mechanisms, specifically behavioral similarity and social proof arguments, interact to impact consumer decision-making in e-commerce. It highlights the importance of aligning recommendation strategies with social cues to boost consumer engagement.

Social/Managerial Contributions: The findings offer practical insights for e-commerce companies seeking to optimize recommender systems. By strategically leveraging behavioral similarity and carefully selecting social proof arguments, companies can more effectively influence consumer behavior and purchasing decisions.

Sustainable Development Goals (SDGs): responsible consumption and production, innovation and infrastructure for digital markets, and sustainable economic growth through informed consumer choices.

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Traduções deste artigo

Efeitos dos argumentos de prova social em Sistemas de Recomendação por filtragem colaborativa (Português (Brasil))

Biografia do Autor

Fábio Roberto Ferreira Borges, Universidade Federal de Minas Gerais (UFMG), Departamento de Ciências Administrativas (DCAD), Faculdade de Ciências Econômicas (FACE), Belo Horizonte, MG, Brasil

Doutor em Administração - Área Mercadologia e Administração Estratégica - pela Universidade Federal de Minas Gerais. Mestre em Administração - Área Mercadologia e Administração Estratégica - pela Universidade Federal de Minas Gerais. Graduado em Administração pela Universidade Federal de Minas Gerais. Possui experiência docente em nível de graduação nos cursos de Administração e Comunicação Social, tendo sido Professor Substituto do Departamento de Ciências Administrativas da UFMG, onde lecionou disciplinas na área de Mercadologia.

Ricardo Teixeira Veiga, Universidade Federal de Minas Gerais (UFMG), Departamento de Ciências Administrativas (DCAD), Centro de Pós-Graduação e Pesquisas em Administração (CEPEAD), Faculdade de Ciências Econômicas (FACE), Belo Horizonte, MG, Brasil

Bacharel em Ciência da Computação, Especialista em Estatística, Mestre e Doutor em Administração - todos os cursos feitos na UFMG. A linha de pesquisa é Mercadologia, Estratégia e Operações. Áreas principais de interesse: teoria de marketing, ética, estética, comportamento do consumidor, pesquisa de mercado e estatística multivariada. Professor Titular do Departamento de Ciências Administrativas da UFMG / FACE e Membro do Corpo Docente Permanente do CEPEAD ( PPGA da Administração). Líder do Tema Marketing de Serviços e Serviços Emergentes, da divisão de Marketing da ANPAD (Associação Nacional de Pós-Graduação e Pesquisa em Administração). Orientou 13 teses de doutorado, 28 dissertações de mestrado, 20 trabalhos finais de curso de especialização, 16 trabalhos de conclusão de curso de graduação e 15 projetos de iniciação científica. No momento, orienta um doutorando, três mestrandos e uma bolsista de IC. Publicou 54 artigos completos em periódicos, 72 trabalhos em anais de eventos, três livros e oito capítulos de livros. Atua como consultor ad hoc do CNPq e Capes, revisor de periódicos de alto impacto nacionais e internacionais e membro do conselho editorial de dois periódicos nacionais.

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