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Studies show that data quality (DQ) issues are extremely costly for companies. To address such issues, as a starting point, there is a need to understand what DQ is. In his context, the 1996 paper “Anchoring data quality dimensions ontological foundations” by Wand and Wang has been highly influential on the understanding of DQ. However, the present study demonstrates that some of the assumptions made in their paper can be challenged. On this basis, this study seeks to develop clearer definitions.

The assumptions behind Wand and Wang’s DQ classification are discussed, on which basis three counter-propositions are formulated. These are investigated through a representation theoretical approach involving analyses of deficient mappings between real-world and information system states. On this basis, an intrinsic DQ classification is derived. A case study is conducted to investigate the value of the developed DQ classification.

The representation theoretical analysis and the case study support the three propositions. These give rise to the development of a DQ classification that includes three primary intrinsic DQ dimensions (accuracy, completeness and conciseness), which are associated with six primary value-level DQ deficiencies (inaccuracy, incorrectness, meaninglessness, incompleteness, absence and redundancy). The case study supports the value of extending Wand and Wang’s DQ classification with the three additional data deficiencies.

By improving the conceptual clarity of DQ, this study provides future research with an improved basis for studies and discussions of DQ.

The study advances the understanding of DQ by providing additional clarity.

Previous studies investigating the effects of using social media in the innovation processes of small and medium-sized enterprises (SMEs) yield mixed results, and the conditions for achieving innovation benefits from social media are unclear. The present study seeks to contribute to the understanding of this topic.

With a basis in the literature on open innovation and SMEs, this study develops a model that explains the role of social media in product innovation processes where technological focus and abilities are converted into product innovations. The model is tested through a survey of 305 Danish manufacturing SMEs.

Findings show that SMEs with higher technological orientation (TO) are more inclined to use social media in their product innovation processes and that social media use explains 22.4 percent of the relationship between TO and product innovation performance. On the other hand, the data did not support the assumption that SMEs with high TO achieve higher product innovation benefits than low TO SMEs for similar levels of social media use.

The results suggest that SMEs with lower levels of TO could increase their product innovation performance through increased use of social media in their innovation processes.

The study provides new knowledge on the role of social media in SMEs’ product innovation processes. As the level of TO increases, the use of social media in the innovation process becomes an increasingly important mechanism for deriving the full innovation potential from technological focus and abilities.