Beschreibung:
According to Global Co-working Growth Study 2020 (Coworking resources, 2020), the numbers of co-working spaces are growing. However, gaining new customers still is challenging, referring to the DeskMag’s report (Kowrk Blog, 2017). From a practical standpoint, this is problematic. This research assumes that if current customers intend to recommend co-working space to new customers, the problem would become less problematic. However, there is no theoretical model that could explain the phenomenon of interest from previous researches. This is a problem from a theoretical standpoint. Therefore, a model, as such, is needed. Thus, this paper develops a conceptual model that could explain what factors drive intention to recommend. The model includes antecedents, overall satisfaction, and intention to recommend. Four statistical analyses were required to analyse the proposed model. Regression analysis was used to test all the relationships, all supported. This becomes a new model that could explain the phenomenon of interest. Then, path analysis was conducted to calculated direct, indirect, and total effects of paths leading to intention to recommend. Then, testing of the indirect effects were carried out to test the effects of antecedents on intention to recommend, all significant. Finally, the total effects were, then, ranked.