5. Conclusion

In this paper, we describe the state-of-the-art of visualization use in Austrian companies from an accounting-related perspective with a focus on Big Data. In particular, we concentrate on novel interactive visualization options (type II visualizations) and analyze their impact on utilization and preference. An analysis of interactive type II visualizations is of importance as the need for an integration of large structured and unstructured data sets into current reporting practices is rising, theoretically favoring their use. Therefore, our objective was to document the current state of adoption with respect to visualization types and interactions techniques, to understand to which extent semi-structured and unstructured data sources are already used by accounting professionals, and how these data sources and structures influence visualization practice and preferences. The latter allows to derive barriers and enablers for adaption, which are clustered in human-related and technology-related factors:

  1. Summarizing the status quo, multiple states of adaption are evident; nevertheless, the majority of companies are still at the beginning stages. Concerning type II visualizations, a mix of types is used with geographical visualizations topping the list. However, their use is still underrepresented compared to type I visualizations. For interaction techniques, filtering is by far the most frequently used technique, however, more advanced techniques such as multiple coordinated views are rarely utilized. Unfortunately, some of the type II visualizations require the utilization of advanced interaction techniques in order to unleash their full potential. Regardless using simple interaction techniques limits EoU of type II visualizations.

  2. With respect to data sources used, traditional data sources (ERP) are by far the most frequently ones used. ERP systems use internal data sources and can be associated with structured data. However, the introduction of additional and semi-structured or unstructured data sources is considerable (e.g. the use of IoT or social media) and the higher their use, the higher the likelihood of including type II visualizations.

    The results obtained by this study and the fact that Big Data (increasing volume, variety and velocity of data sets) is being introduced into everyday business processes show that dispensability of type II visualization is not the cause of the identified gap between research and practice. This vague stage between actual adaption and possible resistance is a solid basis for our analysis and allows us to derive related factors and identify possible barriers.

  3. Both, the lack of familiarity as well as the lack of knowledge with respect to new and interactive visualization options have been identified as human-related barriers. This can first be explained as type II visualizations are more complex and therefore increase the risk of information overload, which in turn results in a selection bias toward already known visualization types. Second, the tendency to rely on already known and rather simple interaction techniques aggravates this problem. This is the case because some of the more complex type II visualizations are inherently built on newer forms of interaction techniques. Only with the use of more advanced interaction techniques can these types release their full potential. Results on the proposed hypotheses in the context of human-related barriers are presented in Figure 9.

    figure 9

    Figure 9.      Results on research model human-related barriers


  4. Technological-related factors did not provide information on potential barriers, with the exception of the sole focus on Microsoft Excel. Instead, these factors seem to be enablers or drivers of adaption. The higher the use of various data sources, the higher the benefits and the necessity of using interactive type II visualizations. Additionally, the higher the use of tools, the easier the access and the inclusion of interactive type II visualizations. In terms of industries, the sole focus on Microsoft Excel is especially high in transportation, communication and electronics (100 percent) as well as in finance, insurance and real estate (60 percent) in our data sample. Results on the proposed hypotheses in the context of technology-related barriers are presented in Figure 10.

    figure 10

    Figure 10. Results on research model technology-related barriers


This study is the first to show how the use of interactive visualization types can be boosted, namely, by the use of technological support (tools) as well as by introducing new and interactive visualization options to the target audience in an appropriate manner. Knowledge on their use is a key in order to enhance their perceived EoU and in turn increase their utilization. Education in accounting needs to incorporate interactive visualization in their curriculums to foster appropriate and widespread use. Also, tools might need to include educational support, e.g. short-videos on the construction, operation and understanding of new visualization option to increase usability, especially when users work with Big Data.

Already identified and very promising areas for interactive type II visualizations in managerial accounting are fraud detection, records and risk management. Further, conventional reporting practice (internal and external) could benefit a great deal, as these visualization types are also task and data optimized for semi-structured and unstructured data sets which are increasingly being used. In conclusion, the mentioned gap between research and practice remains predominant, possibly negatively affecting decision-making in a Big Data related context. However, promising ways to overcome this gap have been localized and suggested in this paper.