semantic differential

Using existing semantic differentials

While it is recommended to apply the framework in full when developing semantic differentials, it may be more selectively applied in studies that make use of existing semantic differentials. Obviously, researchers may conduct confirmatory studies by using an existing semantic differential to investigate the same concept in the same phenomenal context (i.e., population in terms of socio-demographics, nationality, and cultural background; see [1]) as in the original study, either to replicate or theoretically extend existing nomological structures. In such cases, no further testing of whether the semantic differential requirements have been met is necessary if such testing was already done in the study in which the particular semantic differential originated. Applying an existing semantic differential to investigate the same concept, though in a phenomenal context that differs from the one studied in the original article, is another common practice. If the original paper confirms that the focal semantic differential has already passed content validity tests, the available sample of bipolar scales can be considered representative and relevant.

The semantic differential, however, remains a context-specific technique. Therefore, it is recommended that researchers who use existing semantic differentials do pay attention to the following facets of the framework:
1. Bipolarity
2. Wording clarity
3. Unidimensionality
4. Contextual contamination.

Bipolarity and wording pretesting could be added rather easily to pretests already planned in a research project. Dimensionality and contextual contamination could be tested in a small-scale pilot. If for any reason such pilot testing is difficult (e.g., constraints in time, budget, or sample availability), researchers could choose to make use of the data of the final data collection. Scholars considering this approach have to weigh the benefit of increased efficiency against the risks of finding factor solutions that differ from the prespecified theoretical conceptualization and of being confronted with order biases that do demand additional post-hoc statistical remedies [cf. 2].

References used on this page:
1. Berthon, P., Pitt, L., Ewing, M., & Carr, L. (2002). Potential research space in MIS: A framework for envisioning and evaluating research replication, extension, and replication. Information Systems Research, 13(4), 416-427.
2. Podsakoff, P. M., Mackenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.