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intend to purchase, revisit the shopping website) of the consumers [20]. Decision making includes problem solving[2]. Problem solving involves mentally working to overcome obstacles that stand in reaching a goal and arriving at the solution to the problem involves identifying the problem, defining and representing the problem, formulating the strategy , organizing and reorganizing information, allocating resources, monitoring and evaluation[3]. 

Prior research has indicated that (1) task type, (2) individual characteristics, and (3) information presentation format have effects on cognitive processing for making decisions [6]. Decision accuracy, problem comprehension and satisfaction will be used to measure decision making performance. Decision accuracy is probably the most commonly used criterion for measuring decision making performance [22, 35-48]. It is suggested that compared to DG, Dynamic Interactive Graph should facilitate performance [49]. Therefore, this study proposes that DID can enable decision makers to be more accurate when evaluating high volume of data than Dynamic Display.

H1. Compared to Dynamic Display, DID increases users Decision Accuracy

Research in the Management field has not examined different types of visuals and its effect on graph comprehension in detail[6]. The effect of x-y and y-z relationship encoding on the time to comprehend information was studied with respect to2D and 3D line graph [50].

As per Pinker’s theory of Graph Comprehension[51], different types of display are suited for extracting different classes of information, primarily because of two contrasting types of encoding mechanisms governing the graph comprehension process: (1) automatic conceptual message lookup processes and bottom up processing, and (2) inferential and top-down encoding processes. Simplified Flow diagram of the graph comprehension process is shown in Figure 2.

Automatic conceptual message lookup is the acquisition of information using the bottom-up encoding processes where the required information is obtained from the graph easily from the graph by means of salient cues. For example the theory indicated that that trend in a line graph is encoded via the bottom-up encoding processes because the human eye can automatically extract the change perceptually. 

On the contrary, information that are encoded via the inferential and top-down encoding process , needs execution of deliberate and capacity-limited computations that requires effort and use of both short-term and long-term memory processing. Fulfilling comprehension tasks, such as making inferences and drawing conclusions about the data in the graph and selecting and organizing the information from the graph, requires integration of the retrieved and encoded new information. This study proposes that more scan and search operations are needed to visually locate and organize the new information represented in the dynamic graph for both conceptual message lookup process and inferential process. 

The DID possesses interactivity and hence retrieving the information from the graph will be easier for the users by manipulating the data using overview, zoom, filter features of the display. Therefore, in response to the comprehension task, DID will be better than d本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。