Information Technology and Animation

Information Technology and AnimationIntroductionInformation technology (IT) plays a key exercise in creating companionship 1 and supporting management towards determination do2 and Visualization tools be computer applications that produce graphical representations that aid decision making. Visualization tools ar utilize in IT based decision support systems (DSS) the likes of the simple spreadsheets to mingled computer-based systems like business intelligence system, enterprise resource management and reporting system, knowledge management systems, and expert systems to help decision makers to solve structured ,unstructured and semi structured problems. In the digital era, decision makers countenance access to large bill of digital discipline which drive out be enforced by visual analytics software to support decision making. Well structured problem has clear elbow room to beginning but for solving ill structured problem, external representation of the data and the p roblem can reduce the effort in reaching an right solution3. Chief economist of Google Inc predicts that need for data visual image bequeath be growing rapidly in the next few years. He writes. the skill to lend datato be equal to(p) to down the stairsstand it, to run it, to extract value from it, to visualize it, to communicate itthats going to be a hugely outstanding skill in the next decade. because now we re bothy do endure essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it Managers need to be able to access and understand the data themselves 4.Independent researchers have predicted high future posit for visual image tools. Gartners research reports that in spite of global recession businesses are interested in investing in business intelligence (BI) platforms that are expanding their capabilities towards locomote data visualization, scorecards and interactional dashboards. It pr edicts BI markets compound annual growth rate (CAGR) by dint of 2012 to be 7.0% for stand-alone BI platforms (5.Review of the literature on computer graphics as decision aid reports that the format in which data is presented to decision makers is deprecative to return knowledge for making decision6. As per the dual coding theory, cognition consists of two sub systems Visual and Verbal7-9. The theory specifies that when entropy is represented visually, the recall is easier and the human brain can process repositions in shape, color and motion parallely. As per the Central Capacity theory humans have limited working memory 10 and visualization of data (e.g. chart, diagram, graph) activates the visual cistron of the short-term working memory (visual working memory) to hold the visual objects for immediate attention. Both the theory recommend visual data representation to provide instruction to the users for making decisions as visual entropy is easier to store and recall.Vis ualization aids in perceptual information processing to identify exceptions, trends, patterns, relationship in the data (clusters, associations, causality etc), detect outliers and to summarize data perceptually 11. Many complex business decision making need insight and insight is a explosive disc everywherey of a solution to a problem which results in a subjectively catastrophic experience12. As competition in the knowledge economy gets fiercer, organizations are constantly trying to get new insights to gain competitive advantage. Effective visualization tools acts as external aids that supports thinking and building insight by providing graphs that represent information primarily through position, shape, color, size, location, movement and symbols, and that viewers decode that information by pickings it in, organizing it, analyzing it and detecting patterns and structures perceptually13. Human brain is a the right focusing pattern-finding engine and feative graph make behavior al patterns, temporal trends, correlations, clusters, gaps, and outliers visible in seconds and data graphics should amplify cognition and complement what humans do well14. Effective visualization tools are of great importance in supporting decision making as it amplifies cognition, perceptual information processing and facilitates knowledge generation. When visualization tools are inadequate decision making performance is impaired.A review of literature on computer graphics as decision aids has present that decision performance is cause by information presentation format6. Compared to static graph (SG) , propulsive Graph (DG) facilitates in faster retrieval and recall of information 15, 16, information inclusion body 16 required for decision making. One author writes If learners are in control of the speed of animation and can view and review, stop and start, whir in and out, and change orientation of parts and wholes of the animation at willing, then the problems of veridica l perception can be alleviated 17. However the use of energising interactive graph has increased in business decision making, its impact on decision making has not been explored extensively in the IS field. Both the IS literature and Accounting literature has emphasized the need for themeing the role of presentation format in the efficiency and actioniveness of decision-makers decision quality in rewrite to provide empiric evidence on the effect of presentation format on decision quality 18 19. preceding(prenominal) research so far in the IS domain has extensively studied 2D, 3D graph, combining 2D-3D graph and animation with scurvy data volume that are easily comprehensible in delays or graph. Gaining insight from high volume of business data can be challenging because the high density of the data makes it difficult to view all the data at once. On a typical computer screen the high volume data cannot be seen at once, the data has to be sliced to visually represent it on sc reen. A check done on functional mechanisms of online product presentation and its effect on online obtain reported that interactivity of product presentations is a design feature that determine (1) the efficacy of the presentations (2) consumers perceptions of the diagnosticity of websites, their perceptions of the compatibility between online shopping and physical shopping, and their shopping enjoyment derived from a particular online shopping experience jointly deflect consumers attitudes toward shopping at a website and (3) both consumers attitudes toward products and their attitudes toward shopping at a website contribute to their intentions to purchase the products discloseed on the website20.Thus Interactive display has a positive influence on decision making thus the first objective of this muse is extend the work done in the past by studying whether the use of display which has bother interactivity and is dynamic impacts decision making, including reducing information overload when dealing with high volume of data. While indicating a positive l effect from the use of DID, on the basis of the theory of cognitive Fit, which identifies that break out performance results when the external representation corresponds to the nature of the projection to be accomplished 21 this study argues that it is most effective when the qualities of the display corresponds to the salient features of the trade union movement. On Time is also an important component of information load21 where information load is the volume of the data to be treat over the unit of beat available for the occupation.The second objective of this study is to examine weather and how the effect of visualization tools on decision taking may be contingent on the time chastenesss- available time available for information processing. A prior study on 2D graph Vs table to examine the joints effects of presentation format and color on decision accuracy and efficiency under dis analogous ti me constraints 22 concluded that under low time constraints (15 min), tabular reports are better for accurate decision making and 2D graphs are better for faster processing. The combination of Table and graph were better than graph alone for decision accuracy. Under High time constraint (5 min)s color coding led to improved decision making. Decision makers are sometimes pressed for time which can result in information overload, which is the point at which information processing demands exceed the information processing capacity of the individual. This study investigates the moderating effect of time constraints on DID effectiveness on decision making in terms of the quality of the decision that the decision makers are able to make. This study uses the term High Time constraint (HTC) task to characterize the task that needs to nail downd in an environment when the decision makers are under time compel and to distinguish it from Low time constraint (LTC) task where the decision make rs are not under any time stuff to complete the decision making task.Next section contains the review of past work on DID and decision making done to arrive at the hypothesis on the overall impact of DID on decision making. The subsequent section presents a review of the previous litreature on the theory of Cognitive Fit which provides the foundation for our theories on the relationship between diametrical task symbols and DID. Then the disparate task types with time constraints is explained along with the prediction about the moderating effects of task type on decision making. The research method for the proposed research is explained including the measurement of independent and dependent variables and the data-based design. Finally this paper concludes with the significance of this proposed study to both researchers and practioners. conjecture and Hypothesis.The research model developed for this proposed study is shown in figure 1. The figure illustrates that DID enhances deci sion making. The effect of DID is more pronounced when the task is less time critical where the decision makers are not pressed for time and the effect of DID is limited when the task is time critical. The hypotheses back up by theory are developed below. high-power Interactive DisplayBusinesses today are commonly using Dashboards, which is a combination of visualization tools that provide summarized and details reports of current status and alerts and creates situational awareness. The array of visualization tools that available today includes Tree Maps, 23, Node-Link diagram / net profit diagram24, Parallel coordinate Graph 25, Spark lines- Integrates text, and chart 26,Motion chart27. The present study focuses on visualization tools that provide dynamic and interactive display (DID) because in the recent time there has been staggering advances in visualization tools that are interactive and dynamic to support taking decisions and solving information-intensive problems in busin ess. The DID chosen for this study is Googles Motion Chart, which is a flash based visualization tool that delivers dynamic chart with high level of interactivity for multidimensional data28.Motion charts are dynamic. The graph is said to dynamic when the graph consists of series of single frames, each showing incremental changes in the position, brightness, shape, color of the variables shown in a sequence which give the illusion of movement29, 30. Graph Dynamism consist of two types of change position or form 31, 32. Translation change refers to change in position (from one location to another) and understandation change refers to the change in form ( in size, shape, color, brightness)33. Motion chart reflect both interpreting change and transformation change. It is dynamic as it has several indicators which show incremental change in color, location and shape over time.Graphical excellence consists of complex ideas communicated with clarity, precision and efficiency and are ac curately perceive 14. Animations are often not clear and complex or efficient ( too fast) to be accurately perceived and judicious use of interactivity may overcome this disadvantage 17. Motion Chart provide high level of interactivity (i.e., the extent to which users can manipulate and transform the form and content of the graph in real time34. Interactivity is achieved when the users can control the speed of animation and can view and review, stop and start, can transform (change the way representation is rendered, such as zooming, panning or resizing), or manipulate (control the parameters during the process of image generation, i.e. filtering, visually encoding the variables based on color, shape).Decision MakingPrevious study on online shopping website has indicated that dynamic , interactive presentation of information has a positive effect on the shopping decisions ( intend to purchase, revisit the shopping website) of the consumers 20. Decision making includes problem solvi ng2. 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 evaluation3. 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 employ to measure decision making performance. Decision accuracy is in all likelihood 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. at that placefore, 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 interrogation in the attention field has not examined different types of visuals and its effect on graph comprehension in detail6. 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 Pinkers theory of Graph Comprehension51, 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) illative 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 dynamic display.H2a. Compared to Dynamic Display, DID increases users graph comprehension for automatic conceptual message lookup process H2b Compared to Dynamic Display, DID increases users graph comprehension for inferential and top-down encoding process Next from the perspective of affective dimension, users form positive, neutral or negative attitude towards the perceived usefulness of the visualization tool in decision making. The study predicts that DID with interactivity and dynamic display of the multi dimensional data affects decision makers attitude regarding perceived usefulness of the tool more importantly in favor of the tool than dynamic graph. H3 Users attitude towards the perceived usefulness of the DID display differ from their attitude towards the perceived usefulness of the dynamic display.Th eory of Cognitive Fit and Time constraintsThe theory of Cognitive Fit suggest that a match between External representation and users tasks is important for the realization of positive results from the display format 52. While DID generally influences decision making, the degree to which DID affects decision making varies contingent upon the task types being examined. Decision makers may be faced with different types of tasks. Tasks for Problem solving can be retrieval, Communication of facts, Comparison of alternatives, Trend analysis, Recognition and recall, Problem finding, Problem comprehension and Problem solving36. When time in coin decision makers have to make decisions fast and thus decision task can be time critical. In prior studies terms time pressure and time constraint are most commonly used interchangeably 53. Prior research so far has not investigated the time-constraint tasks that are best supported by DID. For this study High Time Constraint (HTC) tasks are those th at force the decision makers to perform under high time pressure. It is different from Low time-constraint (LTC) task for which the decision makers are not under any time pressure to perform. These types of task types moderate the degree to which DDI affects decision making. Research suggests for HTC task , decision makers quicken their processing, are more selective in processing and instead of evaluating one alternative at a time (depth based) the decision makers concentrate on ascribe based ( breadth wide) pattern of processing54. Dynamic Interactive display (DID) have features that lets the users manipulate the data and retrieve details on demand but DID are complex because it provides access to several layers of data which the users can slice and dice. Therefore when DID is used with HTC task , decision makers are unable to accelerate processing as the complexity of the graph makes the users experience information overload , which affects their performance negatively. However when DID is applied to LTC task, then the interactivity is useful because access to several layers of information and availability of time lets the decision makers process information in depth. Thus DID for HTC task does not contribute as much to decision making accuracy, problem comprehension and perceived usefulness as it does for LTC task.H4. Increases in Decision accuracy, effected by DID, are more significant for LTC task than HTC task. H5a. Increases in users graph comprehension for automatic conceptual message lookup process, effected by DID, are more significant for LTC task than HTC task. H5b. Increases in graph comprehension for inferential and top-down encoding process, effected by DID, are more significant for LTC task than HTC task. H6. The impacts of DID on perceived usefulness towards decision making are more significant for LTC task than HTC task.Research MethodThe proposed study will employ a controlled laboratory experiment to empirically test the effects of DID o n Decision making and the moderating effect of time-dependent task types to achieve a high degree of internal validity 55. To simulate experimental display close to real experiences and to increase the generalizability of the findings, instead of develop a prototype of DID , we selected Motion Chart owned by Google Inc for the visualization tool to produce DID . Motion chart is a commercial product used in business.Experimental endFor this proposed study a within-subject factor along with a between-subject factor, 2X2 factorial design will be used. The within-subject factor, Display format, will have two levels DID and Dynamic Graph. The between-subject factor, Task Type will have two levels HTC and LTC (Refer fig 2). The within-subject design for the presentation format will enable control over individual differences like spatial ability56, cognitive style, comprehension abilities, which could confound the results 6 and also economize on the number of participants required for th is study. Fig 2 2X2 Factorial Design Because display format was a within-subject factor, different task type were employed for each display format. The different task will have the same hassle level so that this study can control for difference in task difficulty to have an effect on decision performance. Different task will control for the learning effect that could happen by repeatedly making the same type of decision with same task using different display format under different time dependent task. The participants might not use the interactive features provided in the DID even though it is provided to them. To control for that, the task assigned to DID will require manipulation of the data to arrive at the correct solution and the participants with the correct result will be rewarded with Bonus authorise certificate to motivate them to use the interactive features of DID to arrive at the optimum result. Prior use and practice with a display format has an effect on performance 57 hence to control for that this study will allow participants to have experience with the visualization tool by giving them a brief 15 mins hands on training with the product.As discussed earlier this study uses the term First, the pretest will be conducted with a pilot group that will be demographically similar to the experiment participants to determine the average time required by the subject to reach the optimum solution. Based on this average time the two limits will be chosen to arrive at the High time constraint and low time constraint condition. HTC task is a financial decision making task that will be given to the subjects which involve both bottom up encoding and inferential processing under the High Time constraint in an environment when the decision makers are under time pressure. When there is insufficient time to complete a task, decision performance becomes unpredictable58 and to control for that the subjects in the HTC treatment will be given a time limit which wil l be close to the average time required to reach the optimum solution so that they get sufficient time. Low time constraint (LTC) task is a different financial decision making task that will be given to the subjects which involves both bottom up encoding and inferential processing where the decision makers are not under any time pressure to complete the decision making task. Half of the participants were assigned to Dynamic graph with HCT task and DID with LCT task and the other half in reverse order. Participants were assigned promiscuously to each condition to reduce potential extraneous effects in the experiment.ParticipantsFor the main experiment the participation will be voluntary and the subjects will be selected from the pool of graduate and undergraduate students taking courses in finance, economics or business in a large university. To motivate the subjects to participate in this study they will be offered gift certificates. to encourage their participation in the experime nt. The participants will have to fill out a standard form about their demographics, if they have experience with Motion charts, number of years at the university. For the results to have external validity, this study proposes to conduct the experiment with handful of executives from the industry who are entrusted with the task of decision making to increase the generalizability of results.MeasurementsThe study will use the decision accuracy to measure the decision quality of the decision making performance. As discussed earlier this is a common measure used to measure decision making performance. To measure the problem comprehension this study will employ a authorize comprehension study which has been used in prior studies on effects of information formats 59, 60. To measure perceived usefulness of the display this study will use the validated survey used in prior studies to predict system usage 61. Data AnalysisCronbachs Alpha will be used to survey the reliability of the constr ucts. A repeated measure ANOVA will be run to analyze the effects of information display on decision making. break up t-test will be conducted to compare the mean difference between DID and dynamic display for each of the task type to examine the nature of interaction effects. import of this ResearchThe proposed study can contribute to both theory and practice. By a controlled laboratory experiment , it will empirically test the impact of Dynamic Interactive Display (DID) in decision making performance for high volume of data. Although DID today are available in a number of areas like accounting and finance (Electronic financial statements using XBRL eXtensible Business Reporting Language), geography (E.g. Active Maps), education (E.g. web based active textbook with gay interactive figures), medicine (E.g. Medical imaging), architecture (Floor plan, building plan) but the review of the literature suggests that the impact of DID has not been explored intensively in the IS field. This proposed study aims to provide empirical test of the theory of Cognitive Fit, in supporting that the impact of IT is limited which is contingent on whether a particular IT application, such as DID, is a trustworthy match with the requirement of processing high volume of data to complete a given task. The current study provides useful guidelines for design and use of dense, interactive visualizations towards effective business decision making. If Business want to want to improve decision making performance with high volume of data they can do it with DID. However, because there are so many visualization tools available for use that it is difficult to select the one that is useful for decision making under different time pressure. This proposed study will provide guideline for the usefulness of use DID for HTC and LTC task. These suggestions might help the decision makers and Visualization tool to enjoy the benefits of DID for the appropriate time-dependent task.The proposed stu dy in crucial to understand whether DID has positive effects on decision making and if yes then under what conditions. Interaction can becomes become a compelling tool where users need to filter and zoom on subset of data. There might be information overload and the users might feel lost in the data. There can be added cost in giving access to several levels of data. We also need to understand if providing interactive display is appropriate for tasks which need to be completed under high time pressure and requires processing of high volume of data. This proposed study attempts to imply that DID might not be usable for all decision making context and it is important to understand when it is the most appropriate and use it accordingly to support decision making.References1. 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