Prosocial customer in the public sector: A PLS-SEM analysis applied to blood donation (active donors)

• Published in: Socio-economic planning sciences 2023-04, Vol.86, p.101507, Article 101507
• Main Authors: Robaina-Calderín, Lorena, Martín-Santana, Josefa D., Melián-Alzola, Lucía
• Format: Article
• Language: English
• Subjects: Attitudinal loyalty; Blood donation; Motivations; Obstacles; Service quality
• ISSN: 0038-0121; 1873-6041
• DOI: 10.1016/j.seps.2022.101507

The act of donating blood creates social and public value (as a transformative service), but donors do not always repeat, so this study analyses the antecedents of attitudinal loyalty in donors. In addition, this research identifies active donor profiles to design personalised strategies to increase customers’ attitudinal loyalty. An online survey was conducted with 30,619 active donors who have donated blood at least once over the past two years. The study applies a quantitative modelling model called Partial Least Squares-Structural Equation Modelling (PLS-SEM). Analyses confirmed that motivations, obstacles and service quality influence satisfaction and donor attitudinal loyalty. Also, three active donor clusters were identified, as donation centres must adjust to each cluster to create value for society. This research contributes to understanding the factors that increase donor loyalty and closing a gap in the literature on prosocial consumer behaviour, and thereby other public services that depend upon the willingness of the individual. Furthermore, this approach enables the design of a more effective policy agenda and helps to focus public investment on developing strategies to engage willing and experienced donors. •Donation process, motivations and barriers influence experienced donors' behaviour.•Motivations and barriers continue to influence the donor after several donations.•Findings contributes to understanding donor loyalty and prosocial consumer behaviour.•Conclusions enables the design of a more effective public policy and budget agenda.•A quantitative modelling model Partial Least Squares Equation Modelling is applied.