In 2009, The United States Securities and Exchange Commission (SEC) issued a mandate requiring public companies to provide financial information to the SEC and on their corporate Web sites in an interactive data format using the eXtensible Business Reporting Language (XBRL). This dissertation consists of three separate, but interrelated studies exploring issues related to interactive data visualization in financial reporting contexts. The first study employs theories in information systems (task-technology fit and the technology-performance chain model) and cognitive psychology (cognitive load) to examine the link between characteristics of interactive data visualization and task requirements in a financial analysis context, and the impact of that link on task performance and user attitudes towards interactive data technology use. The second study extends the first by examining the effects of prior interactive data technology use on future choice to use an interactive technology. This study uses the IS continuance model to examine antecedents to continued interactive technology use based on previous assessments of task-technology fit and performance impacts from the first study. The third study employs an elaboration likelihood model (ELM) to understand the interactivity concept and its impact on information processing and belief/attitude formation. This study examines the impact of increasing interactivity on investor perceptions of forecast credibility and on a firm’s attractiveness as a potential investment choice. Overall, these three studies provide insights on factors that impact decision-making in interactive financial reporting contexts, and how characteristics of interactive data visualization impact information processing, user perceptions, and task performance

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隨著互動式資料視覺化工具越來越多，設計者需要一個方法來衡量其作品是否好用、能否被理解、使用效率高低。互動式資料視覺化需要透過使用者的互動才能觀察到資料的不同面向，再進一步產生洞見，然而現有的評估方式多僅聚焦於靜態資料圖表，設計者無法從中得知使用者的操作困難之處，並據此進行加強與改善，因此本研究提出一個整合量化分析與質化記錄的系統性評估方式，應用於互動式資料視覺化的優使性(usability)分析。 本研究的方法為追蹤使用者的眼動和滑鼠操作過程，先將其記錄成量化數據，透過興趣區域的標定與將轉換使用者行為成序列後，進行序列運算和統計分析；同時，從使用者經驗研究方法得到實驗過程的質化記錄，用來輔助解釋量化分析的結果。 本論文藉由兩個互動式資料視覺化工具來驗證以眼動與滑鼠追蹤評估互動式資料視覺化是可行的，我們提出了具體的實驗流程、量化紀錄與分析方式，並建議以下評估指標：吸引力、易發現性、困難度、易識別性、易理解性、精準表達程度、細部困難度、使用效率。 / As more and more interactive data visualization tools emerge, designers need an organized evaluation method to provide timely feedback and understand user behavior. In contrast to traditional graphical presentations, interactive data visualization tools call for user manipulation to gain specific insights. It is therefore imperative to study the intermediate operation process, rather than the final outcome, to provide a critical understanding of the developed tool. Toward this objective, we propose a systematic approach combining quantitative analysis and qualitative assessment to gauge the usability of interactive data visualization tools in this research. Firstly, quantitative data including gaze and mouse movements are collected. By combining the definition of area of interest, these trajectories can be converted into user sequences, which are conveniently accessible for further statistical analysis as well as path comparison. Secondly, qualitative information obtained by observing user operation is gathered to offer additional insight and complement/support conclusions obtained from quantitative analysis. Two interactive data visualization tools are employed to examine the feasibility and universality of our experimental and analytical procedure. To conclude, we come up with several key indicators to evaluate interactive data visualization, including attraction, discoverability, difficulty, identifiability, comprehensibility, precision of expression, difficulty(detailed) and efficiency.