The Effectiveness of Graphical Presentation for Information Extraction: A Cumulative Experimental Approach*

Three laboratory experiments were conducted to assess the relative strengths and weaknesses of bar, symbol, and line graphs for performing a variety of elementary information extraction tasks using two dependent variables, time and accuracy. The findings indicate that the degree of support provided by a particular graph format for a particular data extraction task depends on the matching of format and task in terms of their anchoring characteristics. Anchoring, in this context, refers to the phenomenon that specific and diverse parts of a graph are segmented by the reader to act as salient and relevant cues, or anchors, when different classes of information are to be extracted from the graph. A data extraction task has high x-value (y-value) anchoring if the x-axis (y-axis) component is represented in the question as either a given value or an unknown value. Conversely, a task has low x-value (y-value) anchoring if the x-axis (y-axis) component is not represented in the question as either a given value or as an unknown value. Data extraction accuracy was not significantly affected by presentation format. Bars provided the best time performance for data extraction tasks having high anchoring on both axes but were not appropriate for tasks having low anchoring on either the y axis or both the x and y axes. Line graphs tended to be worse in terms of time performance for tasks having high anchoring on both axes although they were as fast or better than other representations for tasks having low anchoring on both axes. Symbol plots appeared to possess anchoring characteristics associated with both bars and line graphs. Symbols (as with bars) tended to produce a time performance superior to that of line graphs for tasks having high anchoring on both axes; and (as with line graphs) symbols allowed faster results than bar graphs for tasks having low anchoring on either the y axis or both the x and y axes.     

Designing Graphs that Promote Both Risk Understanding and Behavior Change

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk‐avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm (“foreground+background”) versus only those affected (“foreground‐only”), and the presence versus absence of simple numerical labels above bars. Foreground‐only displays were associated with larger risk perceptions and risk‐avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground‐only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground‐only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk‐avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk‐avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground‐only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.     

Swimming Pool Hygiene: Self-Monitoring,Task Clarification,and Performance Feedback Increase Lifeguard Cleaning Behaviors

The effects of task clarification, self-monitoring, and performance feedback on cleaning behaviors of 9 lifeguards in 3 performance areas (vacuuming, lobby tidying, and pool deck maintenance) were investigated using an ABA reversal design at a county swim complex. A specific task in each performance area was used as a behavioral control. Following a task clarification meeting, the percentage of closing tasks completed each night was self-monitored through ratings by lifeguards and managers. Researchers conducted independent ratings of these completed tasks after the staff had left the building. Feedback data were posted daily using line graphs that displayed the percentage of tasks completed correctly from both self-report and researchers' data. Overall performance increased from an average of 45.1% correct behaviors during baseline to an average of 76.9% during intervention then reversed to baseline during follow-up to an average performance of 45.05%.     

Further results on the reciprocal degree distance of graphs

The reciprocal degree distance of a simple connected graph \(G=(V_G, E_G)\) is defined as \(\bar{R}(G)=\sum _{u,v \in V_G}(\delta _G(u)+\delta _G(v))\frac{1}{d_G(u,v)}\), where \(\delta _G(u)\) is the vertex degree of \(u\), and \(d_G(u,v)\) is the distance between \(u\) and \(v\) in \(G\). The reciprocal degree distance is an additive weight version of the Harary index, which is defined as \(H(G)=\sum _{u,v \in V_G}\frac{1}{d_G(u,v)}\). In this paper, the extremal \(\bar{R}\)-values on several types of important graphs are considered. The graph with the maximum \(\bar{R}\)-value among all the simple connected graphs of diameter \(d\) is determined. Among the connected bipartite graphs of order \(n\), the graph with a given matching number (resp. vertex connectivity) having the maximum \(\bar{R}\)-value is characterized. Finally, sharp upper bounds on \(\bar{R}\)-value among all simple connected outerplanar (resp. planar) graphs are determined.     

Do auditors’ perceptions actually help fight against fraudulent practices? Evidence from Tunisia

The purpose of this paper is focused on investigating empirically how Tunisian Auditors perceive their status regarding fraud fighting issue. In this respect, a set of auditor-associated mental representations will be expressed in terms of their respective roles as relevant governance models (legal versus ethical ones), via the cognitive mapping technique. The findings reveal that corporate governance can be globally depicted within these particular representations, indicating the supremacy of the legal governance approach over the ethical one with regard to the Tunisian case. .     

What's Time Got to Do with It? Inattention to Duration in Interpretation of Survival Graphs

Reports of randomized clinical trials often use survival curves to summarize clinical outcomes over time and graphically demonstrate evidence of treatment effectiveness. Survival curves can also be used in patient communications to display how health risks accumulate over time. In a randomized survey experiment, administered online, we tested whether people viewing survival curves appropriately adjust their risk perceptions to account for the duration shown. Internet users (N= 864) were recruited from a demographically balanced U.S. panel. Participants read about a hypothetical disease and then viewed one of four survival graphs that displayed mortality risks with and without treatment. Survival graphs showed either a visually large or visually small difference between treatments and were labeled to represent either 5-year or 15-year risk statistics. Participants then provided ratings of disease seriousness, as well as treatment effectiveness for each possible treatment. Variations in ratings corresponded more with visual dissimilarity than with changes in the statistical risk exhibited, with participants perceiving somewhat greater disease seriousness and significant differences in treatment effectiveness in large visual difference graphs. We conclude that when people interpret survival curves, they often fail to sufficiently account for the timeframe represented and perceive more risk and larger differences when identical risks are displayed over longer periods of time. We recommend that all presentations of survival graphics, whether to patients, physicians, or scientists, emphasize duration information (e.g., in the title) and remind readers that attending to graph axis labels is the only way to pierce these visual illusions.     

Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making

Previous research suggests that the choice of graphical format for communicating risk information affects both understanding of the risk magnitude and the likelihood of acting to decrease risk. However, the mechanisms through which these effects work are poorly understood. To explore these mechanisms using a real‐world scenario, we examined the relative impact of two graphical displays for depicting the risk of exposure to unexploded ammunition during potential land redevelopment. One display depicted only the foreground information graphically (a bar graph of the number of people harmed), and a second depicted the foreground and background graphically (a stacked bar graph representing both the number harmed and at risk). We presented 296 participants with either the foreground‐only or the foreground and background graphical display and measured a broad set of outcome variables, examining (1) the graphical display effect on each of the outcome measures and (2) the pathways by which any display effects work to influence decision making. We found that the foreground‐only graphical display increased perceived likelihood and experienced fear, which produced greater worry, which in turn increased risk aversion. In addition, a positive evaluation of the communication materials increased support for policies related to land redevelopment, whether those policies were risk taking or risk mitigating. Finally, the foreground‐only graphical display decreased understanding of the risk magnitude, showing that approaches to accomplish one risk communication goal (promoting risk‐averse decisions) may do so at the expense of another goal (increasing understanding).     

Re-forming the traditional organization medical staff

The traditional, two-bylaws-model organized medical staff was created in another age (1919) to serve a simple health care system, controlled by physicians, in which the only players were patients, doctors, nurses, and small hospitals. This medical staff model does not meet the needs of the U.S. health care system of the 1990s. The purpose of this article is to provide the physician executive with a resource to use when he or she is called on to help determine what, if any, changes are needed in his or her organization to make the role of physician leaders more effective. Finding the right answer to this question is part of discovering ways to reduce health care costs without reducing the funds available to pay for direct delivery of health care services. Maintaining traditional, bureaucratic, legalistic organized medical staff activities is a very expensive game that we can no longer afford to play.     

An Evaluation of Stimulus Preference Assessment Methodology in Organizational Behavior Management

The organizational behavior management literature has yielded few stimulus preference assessment methodologies for use with employees. The current investigation compared three preference assessments (ranking, survey, and multiple stimulus without replacement procedures) found in the organizational behavior management literature for their ability to predict reinforcers for direct care staff members’ behavior. In the first experiment all assessments were effective for predicting reinforcers, but the results were limited by a lack of control items in the assessment. In the second experiment the survey and ranking assessments both proved to be effective for identifying reinforcers and neutral or ineffective stimuli. Implications of these results and directions for future research are discussed.     

Regulatory Trade Risk and Supply Chain Strategy

Trade regulations are an important driver of supply chain strategy in many industries. For example, the textile, paper, chemical, and steel industries grapple with significant levels of non‐tariff barriers (NTBs) such as safeguard controls and countervailing duties. We explore three often observed supply chain strategies in industries subject to NTBs; direct procurement, split procurement, and outward processing arrangements (OPAs). We characterize the optimal procurement quantities for each of these three strategies, and examine how industry and country characteristics influence the firm's strategy preference. For example, we establish that the direct and split strategy profits increase in the NTB price variance but decrease in the mean price. These effects are sufficiently large that NTB price characteristics can dictate which supply chain strategy is preferred. Both the cost disadvantage and lead‐time advantage of domestic production are also significant influencers of the preferred strategy, as is the domestic‐country mandated production constraint associated with the OPA strategy.     

A Further Evaluation of Response Cards: Teaching Direct Care Staff Basic Behavioral Principles

Numerous studies have demonstrated the efficacy of response cards for teaching students in educational settings; however, the effectiveness of response cards has yet to be examined in organizational settings where such strategies may be very useful (i.e., in staff training). The purpose of this study was to evaluate the utility of response cards during in-service training to teach basic behavioral principles to direct care staff working in a human service setting. Results indicated that individuals who received the response card training participated more during training and were able to retain more information over time relative to those who received a standard in-service training.     

Graphic Feedback,Performance Feedback,and Goal Setting Increased Staff Compliance With a Data Collection Task at a Large Residential Facility

Because of budgetary constraints, human service organizations frequently expect consultants to recommend methods to enhance staff performance that require little or no additional funding. The current study utilized a multiple baseline across settings design to evaluate and compare the effects of a single intervention and a packaged intervention including graphic feedback and goal setting on approximately 200 direct care staff as a group, to improve the data collection procedure at a residential treatment facility. The single intervention showed some improvement, whereas the packaged intervention yielded substantial improvements and was maintained.     

Efficient identifications of structural similarities for graphs

Measuring and detecting graph similarities is an important topic with numerous applications. Early algorithms often incur quadratic time or higher, making them unsuitable for graphs of very large scales. Motivated by the cooling process of an object in a thermodynamic system, we devise a new method for measuring graph similarities that can be carried out in linear time. Our algorithm, called Random Walker Termination (RWT), employs a large number of random walkers to capture the structure of a given graph using termination rates in a time sequence. To verify the effectiveness of the RWT algorithm, we use three major graph models, namely, the Erd?s-Rényi random graphs, the Watts-Strogatz small-world graphs, and the Barabási-Albert preferential-attachment graphs, to generate graphs of different sizes. We show that the RWT algorithm performs well for graphs generated by these models. Our experiment results agree with the actual similarities of generated graphs. Using self-similarity tests, we show that RWT is sufficiently stable to generate consistent results. We use the graph edge rerouting test and the cross model test to demonstrate that RWT can effectively identify structural similarities between graphs.     

An Initial Assessment of Effective Preference Assessment Intervals Among Employees

Previous research has shown that employee preferences for tangible items may change significantly from one month to the next. Although a 1-month interval may be too long to wait between preference assessment administrations, no guidelines exist with regard to how often to assess employee preference. This study examined changes in preference as measured by two different preference assessments across four different time intervals. We measured preference stability by assessing changes in designations of high- and low-preference items from one assessment to the next. Only the 1-week interval indicated no changes in item designation from high preference to low preference or low preference to high preference. These data suggest that if tangibles are used, preferences may need to be assessed over time.     

Fibonacci index and stability number of graphs: a polyhedral study

The Fibonacci index of a graph is the number of its stable sets. This parameter is widely studied and has applications in chemical graph theory. In this paper, we establish tight upper bounds for the Fibonacci index in terms of the stability number and the order of general graphs and connected graphs. Turán graphs frequently appear in extremal graph theory. We show that Turán graphs and a connected variant of them are also extremal for these particular problems. We also make a polyhedral study by establishing all the optimal linear inequalities for the stability number and the Fibonacci index, inside the classes of general and connected graphs of order n.     

Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences

In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the concept of efficiency with respect to preference information.     

Non-convex value efficiency analysis and its application to bank branch sales evaluation

We have observed when applying Value Efficiency Analysis [21] that decision makers wish to provide preference information related to existing rather than virtual (efficient) units. This observation motivated us to develop an approach based on the preference comparisons of existing units. The Free Disposal Hull model provides the requisite framework. We assume that a Decision Maker compares units using an implicitly known value function that reaches its maximum at his/her most preferred (efficient) unit. The unknown value function is assumed to be quasi-concave in outputs and quasi-convex in inputs. The main purpose – as in the original Value Efficiency Analysis – is to approximate the distance of each unit from the contour of the value function passing through the most preferred unit. We use examples to illustrate the approach. Finally, we describe a real application in which Value Efficiency Analysis was used to produce information for bank managers wishing to evaluate the performance of bank branches.     

Incremental and Average Cost‐Effectiveness Ratios: Will Physicians Make a Distinction?

Physicians are increasingly asked to use cost-effectiveness information when evaluating alternative health care interventions. Little is known about how the way such information is presented can influence medical decision making. We presented physicians with hypothetical screening scenarios with multiple options, varying the type of cost-effectiveness ratios provided as well as whether the scenarios described cancer screening settings that were familiar or unfamiliar. Half the scenarios used average cost-effectiveness ratios, as commonly reported, calculating benefits and costs relative to a no-screening option. The other half used the preferred incremental cost-effectiveness ratios, with each option's benefits and costs calculated relative to the next best alternative. Relative to average cost-effectiveness ratios, incremental cost-effectiveness information significantly reduced preference for the most expensive screening strategies in two of three unfamiliar scenarios. No such difference was found for familiar scenarios, for which physicians likely have established practice patterns. These results suggest that, in unfamiliar settings, average cost-effectiveness ratios as reported in many analyses reported in the literature can hide the often high price for achieving incremental health care goals, potentially causing physicians to choose interventions with poor cost effectiveness.