Advancing PR measurement and evaluation: Demonstrating the properties and assessment of variance-based structural equation models using an example study on corporate reputation

What is it about?

Finding appropriate measures for PR outcomes—such as an organization’s image, reputation, or trustworthiness—remains a demanding task. These constructs are complex intangibles that have to be defined, specified, and measured carefully to produce meaningful results for an organization. But it gets more complicated: Merely descriptive analyses of an organization’s image, reputation or trustworthiness cannot explain what PR evaluators ultimately want to know, which is: how exactly these intangibles contribute to the building of trust-based relations, the facilitation of favorable stakeholder behavior, or even the creation of economic value added. Without taking into consideration this wider causal network of variables, it is not possible to fully evaluate the role and importance of PR outcomes. Such causal networks can be analyzed by applying the method of structural equation modeling (SEM). Our article introduces the properties of one of the two major SEM approaches (PLS-SEM) and demonstrates, step by step, how it can be gainfully applied to PR research and evaluation.

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Why is it important?

Finding appropriate measures for PR outcomes—such as an organization’s image, reputation, or trustworthiness—remains a demanding task. These constructs are complex intangibles that have to be defined, specified, and measured carefully to produce meaningful results for an organization. But it gets more complicated: Merely descriptive analyses of an organization’s image, reputation or trustworthiness cannot explain what PR evaluators ultimately want to know, which is: how exactly these intangibles contribute to the building of trust-based relations, the facilitation of favorable stakeholder behavior, or even the creation of economic value added. Without taking into consideration this wider causal network of variables, it is not possible to fully evaluate the role and importance of PR outcomes. Such causal networks can be analyzed by applying the method of structural equation modeling (SEM). Our article introduces the properties of one of the two major SEM approaches (PLS-SEM) and demonstrates, step by step, how it can be gainfully applied to PR research and evaluation.