Information Extraction From Different Data Representation Forms: Charts and Tables

Presenting data in the form of graphs and tables has long been considered as an important tool for decision making. Extracting information from these presentation forms are considered to be cognitively intensive tasks. Prior research works on aspects of presentation forms have produced inconsistent and conflicting results. In this study, we examine effects of tabular and graphical (bar, line, and pie) forms on information extraction. Graphs were examined with solid and textured patterns as well. We conducted a laboratory experiment where in subjects answered set of questions which would require them to extract information from the presentation display. Our study reveals that tables, even though they have higher response rate, produced more accurate results than graphs. Comparison within graphs showed that bar charts had a lower response rate than pie and line charts, while pie charts produced the least accurate results. Comparison of solid and textured patterns in graphs revealed that they are not an influencing factor in regards to information extraction. We also provide detailed comparison of current research findings against to prior research results

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like.Learning;Feedback;Marketing Decision Models;Marketing Decision Support Systems;Marketing Information Systems

The Effects Of Decision Framing Influences On Decision Performance

This study investigates the effects of two components of decision framing [commitment and verbalization] in decision optimization, and how information quality impacts framing effects on decision performance.  The theory of cognitive dissonance predicts that commitment to a decision will foster insensitivity to alternative choices.  We find that such bias can be beneficial in certain decision strategies, and more powerfully influential as information quality worsens.  We used an interactive computer simulation to test decision framing effects in a profit optimizing business simulation and to examine the magnitude of the framing effect under varying conditions of information quality, which was proxied as cost information type (ABC: higher quality; VBC: lesser quality). The influences of these factors were tested on the profit optimizing abilities of 48 accounting majors under controlled, laboratory conditions.  Results showed that framing influences improved decision-making, and the effects of framing influences were more powerful in decision environments of poorer quality information [VBC] than in higher quality decision environments [ABC].  Framing was most supportive of decisions when most needed, poor information environments, and not of significant influence in clearer decision environments. 

An information assistant system for the prevention of tunnel vision in crisis management

In the crisis management environment, tunnel vision is a set of bias in decision makers’ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the challenges in the task and the natural limitation in a human being’s cognitive process. An information assistant system is proposed with the purpose of preventing tunnel vision. The system serves as a platform for monitoring the on-going crisis event. All information goes through the system before arrives at the user. The system enhances the data quality, reduces the data quantity and presents the crisis information in a manner that prevents or repairs the user’s cognitive overload. While working with such a system, the users (crisis managers) are expected to be more likely to stay aware of the actual situation, stay open minded to possibilities, and make proper decisions

Role of Visualization in a Knowledge Transfer Process

Background: Efficient management of the knowledge requires implementation of new tools and refinement of the old ones - one of them is visualization. As visualization turns out to be an efficient tool for transfer of acquired knowledge, understanding of the influence of visualization techniques on the process of knowledge sharing is a necessity. Objectives: The main objective of the paper is to deepen the understanding of the relation of visualization to other knowledge sharing paths. The supplementary goal is a discussion of constraints on visualization styles in relation to readability and efficiency. Methods/Approach: Due to the ambiguous nature of the problem, case analysis was selected as a research method. Two research papers have been selected for that. The first one focused on agrotourism, introduces a general use theoretical tool suitable for various purposes, such as consumer sentiment analysis. The second one evaluates possibilities of revealing an implicit organizational structure of an organization by means of visual analysis using interaction graphs. Results: Visualization is an important part of data analysis and knowledge transfer process. Hybrid visualization styles enhance information density but may decrease clarity. Conclusions: In order to maximise the role of visualization in a knowledg tranfer process, the special care must be devoted to clarity, the optimal level of details and information density in order to avoid obfuscation

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like

USE OF VISUALIZATION IN DIGITAL FINANCIAL REPORTING: THE EFFECT OF SPARKLINE

Information visualization (InfoViz) is an essential component of decision support systems (DSS). Sparklines is a visualization tool. This study examines if Sparklines in digital financial reports aids novice investors and if so under what circumstances? Does it enhances decision-making performance and facilitates effective decision-making experience? Additionally, does it lowers decision making effort; reduces dilution effect from non-relevant data in financial reports and mitigates recency bias in using digital financial reports? The hypothesis is guided by the theory of Proximity Compatibility Principle and the Theory of Cognitive Fit. The research methodology for this study is a repeated measure, controlled laboratory based experiment. A pilot test was conducted in with a sample of forty undergraduate students from Gatton College of Business and Economics. The sample size for this study was 275 subjects. The result revealed that there was significant effect of sparklines on decision making performance and it provides an incremental value over a tabular format. Sparklines makes an important contribution towards mitigating recency bias. The results also suggested that the irrelevant information cue in the shareholder’s report were not able to weaken the impact of relevant information in the audited financial data reported using sparklines. Sparklines increased the attention of the readers to the tables. Subjects performed the integrative tasks and spatial better when using Sparklines. For tasks such as symbolic tasks, Sparkline does not necessarily improve decision performance. It was also found out that decision makers experience greater satisfaction when using sparklines. The overall cognitive load experienced by subjects was lower using sparklines when task demands are high (such as in a bankruptcy prediction task). Interestingly, the results indicate that there is no significant effect of sparkline on decision confidence and time. In conclusion, recall of facts and pattern among subjects was found superior with use of sparkline. This study provides an empirical and justifiable basis for policy makers to make explicit recommendations about use of novel graphics such as sparkline in digital financial reports. Limitations of this study are noted

The Powerful Triangle of Marketing Data, Managerial Judgment, and Marketing Management Support Systems

In this paper we conceptualize the impact of information technology on marketing decision-making. We argue that developments in information technology affect the performance of marketing decision-makers through different routes. Advances in information technology enhance the possibilities to collect data and to generate information for supporting marketing decision-making. Potentially, this will have a positive impact on decision-making performance. Managerial expertise will favor the transformation of data into market insights. However, as the cognitive capabilities of marketing managers are limited, increasing amounts of data may also increase the complexity of the decision-making context. In turn, increased complexity enhances the probability of biased decision processes (e.g., the inappropriate use of heuristics) thereby negatively affecting decision-making performance. Marketing management support systems, also being the result of advances in information technology, are tools that can help marketers to benefit from the data explosion. These systems are able to increase the value of data and, at the same time, make decision-makers less vulnerable to biased decision processes. Our analysis leads to the expectation that the combination of marketing data, managerial judgment, and marketing management support systems will be a powerful factor for improving marketing management. Implications of our analysis are discussed.decision making;decision biases;information technology;marketing management support systems

Advanced Decision-Oriented Software for the Management of Hazardous Substances: Part III - Decision Support and Expert Systems: Uses and Users

Many industrial processes, products, and residuals such as hazardous and toxic substances, pose risks to man and are harmful to the basic life-support system of the environment. In order to reduce risks to individuals and society as a whole, and to ensure a sustainable use of the biosphere for present and future generations, it is imperative that these substances are managed in a safe and systematic manner. The aim of this project is to provide software tools which can be used by those engaged in the management of the environment, industrial production, products, and waste streams, and hazardous substances and wastes in particular. This set of tools is designed for a broad group of users, including non-technical users. Its primary purpose is to improve the factual basis for decision making, and to structure the decision-making process in order to make it more consistent, by providing easy access and allowing efficient use of methods of analysis and information management which are normally restricted to a small group of technical experts