Understanding alumni loyalty from a relational marketing approach

Abstract

Iskhakova, Hoffmann and Hilbert (2017) identify the benefits of a close university-Alumni relationship. On the one hand, material benefits are donations or financial contributions and repurchase behavior based on the lifelong learning theory. On the other hand, non-material benefits are levels of commitment and loyalty of Alumni towards the university. Some of these benefits are: (a) the professional profile of the university's graduates for the accreditation processes, (b) the positioning of the university in the labor market, (c) the direct connection with organizations, and (d) voluntary participation in aspects such as teaching, mentoring and
tutoring that provide a better learning experience for students (Hummel, 2010; López & Jaramillo, 2020). It is safe to recognize Alumni as one of the university's main stakeholders. That is why managing the relationship and communication with them is critical. Faced with this need, many educational institutions use relationship marketing to resolve it. Relationship marketing is the creation of a strategy that seeks to attract and retain relationships with the main stakeholders (Mallada & Colom, 2010; Palacio & Rondón, 2018; Schlesinger, Cervera & Iniesta, 2012).

This article seeks to understand the university-Alumni relationship by applying the Alumni-University Identification Model proposed by Schlesinger, Cervera, Iniesta & Sánchez (2014) and Schlesinger et al. (2012). This model is based on relationship marketing and seeks to understand the quality of interactions between the university and its Alumni. In the same way, the level of identification Alumni has with their alma mater. Furthermore, how this affects their commitment and loyalty to the university. The case study is in the Pontificia Universidad Católica del Perú (PUCP university) and Alumni from its School of Management.

This research will use a quantitative approach to seek to test the hypotheses of the relationship between factors raised by Schlesinger et al. (2014). The estimation of the relationships will be done under the structural equation model using the partial least squares regression method. The information collected to meet the research objectives will be through a questionnaire based on Schlesinger et al. (2014), whose constructs present high levels of reliability, aimed at students who graduated between the periods 2010 - 2019 from the School of Management of the PUCP.