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Knowledge advancement occurs when the creation of new and useful knowledge encompasses and supersedes earlier knowledge. A rapidly growing number of scholars with state-of-the-art research tools has led to the growth of knowledge exploration in almost every field. It, however, has been observed that the findings of new studies frequently

Knowledge advancement occurs when the creation of new and useful knowledge encompasses and supersedes earlier knowledge. A rapidly growing number of scholars with state-of-the-art research tools has led to the growth of knowledge exploration in almost every field. It, however, has been observed that the findings of new studies frequently differ from previously established evidence and even disagree with one another. Conflicting and contradictory results prevail in the literature. This phenomenon has puzzled many people with respect to which findings are reliable and which should be considered as valid. Inconclusive results in the literature inhibit, rather than facilitate, knowledge advancement in sciences. Meta-analysis, which is referred to as the analysis of analyses, designed to synthesize findings from a large collection of quantitative analyses that produce inconsistent results has become a major research method in the fields of medicine, education, and psychology; however, the method has been slow to penetrate research in nonprofit and public management (NPM). This study, therefore, discusses how meta-analysis contributes to knowledge advancement in the fields of nonprofit and public management by using nonprofit commercialization as an example to examine its impact on nonprofit capacity and donations, respectively. The attention of this discussion is directed toward how the use of meta-regression models is able to offer new and useful knowledge that encompasses and supersedes earlier knowledge in the literature with evidence-based results. Moreover, this study examines whether the use of SEM-based meta-analysis produces equivalent results when compared with results from traditional meta-regression models. The comparison results suggest that the use of SEM-based meta-analysis is able to produce equivalent results even when missing data are present. Overall, this study makes at least two contributions. First, it introduces a newly-developed method for conducting meta-analysis to the field of NPM. This method is especially useful when there are missing data in data sets. Second and most importantly, this study demonstrates how knowledge advancement in NPM can be achieved by conducting meta-analysis.
ContributorsHung, Chia-Ko (Author) / Hager, Mark (Thesis advisor) / Lecy, Jesse (Committee member) / Wang, Lili (Committee member) / Calabrese, Thad (Committee member) / Arizona State University (Publisher)
Created2019