A combined importance-performance map and necessary condition analysis of the acceptance of blockchain use in marketing: the case of loyalty programmes

Blockchain technology has applications beyond cryptocurrencies, notably in marketing through blockchain-based loyalty programmes (BBLPs). This study examines key factors for their implementation using importance-performance map analysis (IPMA) and necessary condition analysis (NCA), based on an adap...

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Detalles Bibliográficos
Autores: de Andrés Sánchez, Jorge, Arias Oliva, Mario, Souto Romero, Mar, Llorens Marín, Miguel
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/125826
Acceso en línea:https://hdl.handle.net/20.500.14352/125826
Access Level:acceso abierto
Palabra clave:blockchain
blockchain-based loyalty programmes
PLS-SEM
importance-performance map analysis
necessary condition analysis
Ciencias Sociales
53 Ciencias Económicas
Descripción
Sumario:Blockchain technology has applications beyond cryptocurrencies, notably in marketing through blockchain-based loyalty programmes (BBLPs). This study examines key factors for their implementation using importance-performance map analysis (IPMA) and necessary condition analysis (NCA), based on an adapted TAM3 model. The key endogenous variables include behavioural intention to use (BEINT), perceived usefulness (USEF), and perceived ease of use (EASE). The model suggests that USEF mediates the effects of trust (TRUST) and price-value (PVAL) on BEINT, while EASE mediates self-efficacy (SEFFIC) and perceived enjoyment (PENJ). Structural equation modelling reveals that USEF, EASE, PVAL, SEFFIC, and PENJ significantly impact BEINT. TRUST influences USEF but not BEINT directly, and social norms (SNORM) are not significant. IPMA analysis identifies USEF as the critical variable for BBLP acceptance, with EASE and PENJ being key influencers, followed by PVAL. NCA and IPMA findings show that all variables, except SNORM, can act as constraints to increasing BEINT. However, TRUST and SEFFIC exceed the necessary threshold, indicating they are not actual constraints. Conversely, USEF, EASE, and PENJ act as bottlenecks, with USEF being crucial for BEINT improvement, while EASE and PENJ enhance perceived usefulness. Strengthening these factors can drive BBLP adoption.