However, they also evidence that there is no additional benefit in financial reporting understandability when simultaneously providing both explanations of technical jargon and visual aids. Further research is, therefore, necessary for a better assessment of how and to what extent the use of graphs or visuals enhances understandability of accounting reports. Thus, our third hypothesis that infographics could improve users' actual understanding of financial reporting cannot be supported.
Adherence to a reasonable level of understandability would prevent an organization from deliberately obfuscating financial information in order to mislead users of its financial statements. The questionnaire was administrated to three European countries that adopt accrual accounting reporting systems at the local government level. Greece, Italy and Spain fall into the Continental European Napoleonic administrative classification and they do not have a tradition of publishing reports specifically developed for citizens (Bastida et al., 2022).
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Research in corporate reporting shows that users find graphical information displayed in annual reports very useful as they make financial information more easily understood (Mohd Isa, 2006). However, research demonstrating that the same benefits are also evident in relation to public sector financial accounting information is still in its infancy. Langella et al. (2021) provide evidence that graphical and visual representations increase financial statements' understandability.
For more details on stochastic operational models, we refer to standard textbooks such as [557] (check also for Chapter 8.3.1). Research on probabilistic causation in operational models, such as MDPs and Markov chains, is comparably rare. An exception is the work by Kleinberg [985,986], who formalized probabilistic causation in the context of temporal logics for Markov chains to infer complex causal relationships from data and to explain the occurrence of actual events. In [985], a notion of prima facie causes that relies on requirements formalized as formulas of Probabilistic Computation Tree Logic (PCTL) has been introduced. To reason about probabilistic causation in Markov chains, [985] combines standard PCTL model checking [584] with statistical hypothesis testing.
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And so, highly valuable information such as usage patterns, real-world inputs and outputs, and actual performance and availability statistics can become accessible to teams determined to have them. In such organizations, understandability takes on an even more powerful form, determining how well engineers can understand how the software operates and how it is being utilized by the application’s customers. As a result, David reconsidered his judgment and changed it from good to satisfactory. Then he continued producing prototypes until he obtained a response time of 0.1 ms, which he considered good even taking new insights into account. Then he again showed the prototype to Sean; this time Sean also felt the response time was good.
Take it one step further, and you’ll find that your software’s complexity is derived from a large amount of developers writing a lot of code. Simply put, the more code that’s written, the more complex and interdependent it becomes. It becomes harder to comprehend its behavior and, unfortunately, much more difficult to get the data you need from that code to help you understand what’s going on in there.
So, the results confirm that infographics can be useful to understand changes or patterns in data (Beattie and Jones, 2001; Harris, 2000) and the importance of visual appeal to meet citizens' information needs (Yusuf and Jordan, 2012). Consequently, this result can contribute to the literature on popular reporting, to better understand the benefits deriving from the inclusion of infographics in these reports. Our analysis provides corroborative evidence that users rate infographics better compared to traditional financial statements as a presentation format to convey accounting information.
- Then he again showed the prototype to Sean; this time Sean also felt the response time was good.
- However, they also evidence that there is no additional benefit in financial reporting understandability when simultaneously providing both explanations of technical jargon and visual aids.
- Pearl's probability-raising approach [973] relies on the distinction between observation and intervention, where the latter overrides the original model and zooms into what would have happened if system variables are forced to take a certain value.
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- Systems can be reduced from the “top” by focusing on the business requirements that truly matter, while leaving out, at least temporarily, requirements that are not mandatory.
In addition, our decision to split the sample into two subgroups based on the respondents' self-assessment regarding accounting knowledge and financial statements familiarity may sound subjective. Future studies could benefit from this limitation and try acknowledging accounting knowledge and familiarity through objective measures. Finally, our sample includes participants that have adequate knowledge of accounting and familiarity with financial statements which might not be representative of the profile of an average citizen-user. In this realm, we also propose the engagement of citizens in the design of financial documents according to their specific interests and needs which is expected to increase the use of the information.
When understanding your software, making sure that it’s secure is of absolute importance. Standards and general regulations (while often quite annoying to adhere to) need to be complied with so that you can create comprehensible software. In order to achieve understandability, we highly recommend that you understand what is at its core. There are four key characteristics that need to be present in order to obtain understandability into your software. Now, I know you’re probably thinking to yourself- well, understanding my code sounds pretty great – but where on earth do I start?
The less you understand, the more you will find yourself relying on other people, struggling to collect more information. If all else fails, you just may find yourself pushing log lines to production to try and figure out what is going on. We all had that eureka moment where a colleague approached us to report a bug, and even before we finished the sentence, we knew what was wrong and in which line of code should fix it. Unfortunately, in complex software environments, more often than not, that’s not the case. Regardless of its source, complexity hurts engineers’ ability to understand and effectively change the software as needed.
