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Development of a Causal Alumni Loyalty Model: Cross-cultural and Cross-gender investigations

Alumni loyalty is a relevant research field, which includes different possibilities for investigation. This dissertation focuses on the particularly relevant research gaps in the AL literature. Specifically, this thesis adds to the AL research by developing a more accurate conceptual IAL model for the explanation and prediction of AL. This model includes main internal and external factors (i.e., gender and culture) and could serve as a basis for further theoretical research or could be applied in practice as it is.
The findings of this thesis provide deeper insight into the mechanism of alumni university interactions and help to implement an effective, pragmatic plan of AL by taking into consideration cross-cultural and cross-gender differences of alumni. Specifically, the dissertation could be beneficial to educators, researchers, and managers. Educators could integrate the pertinent information into their teaching materials for courses in non-profit marketing and management. Researchers could use the provided reference tool and obtained findings to identify colleagues with similar research interests, to recognize directions for future investigation into the subject, and to develop a deeper and more detailed understanding of AL. The managers could use the results of this dissertation to determine areas which need to be stressed to enhance AL. Additionally, the derived ideas and strategies of AL could assist managers in better analyzing nonprofit organizations and developing an in-depth understanding of the commonalities across various types of alumni groups, “and patterns in the differences among them” (Pettit, 1999, p. 105).
The author of this thesis believes that the dissertation can bring “a new era to alumni research” by developing a body of research-based knowledge about a variety of important issues related to AL (Pettit, 1999, p. 105).

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:72585
Date29 October 2020
CreatorsIskhakova, Lilia
ContributorsHilbert, Andreas, Siems, Florian, Schirmer, Frank, Technische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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