Risk Framing in Performance Measurement Systems: The Effect on Risky Decision-Making

To address the limitations of the traditional performance measurement systems (PMSs) in visualizing risk and preventing excessive managerial risk-taking, a number of research studies proposed to extend the functionality of PMSs by incorporating risk measures and goals and thereby enabling a better view on organizational risk exposures. While researchers still continue to provide claims regarding the benefits of a balanced approach to combined risk and performance representation in PMSs, the literature still lacks a uniform vision about the design of such risk-aware PMS and about how effective it is in the context of making risky decisions. In this study, a laboratory experiment was conducted to investigate how framing risk through strategic goals and key indicators incorporated in a PMS affects risky decision-making. The findings demonstrated a significant direct effect between PMS problem frame and risky decision-making. Specifically, the choice of a PMS frame with performance-driven strategic goal (emphasizing organizational focus on increasing gain/performance) and no risk measure was proved to result in a higher level of managerial risk taking compared to the choice of a risk-aware PMS frame which adopted a risk-driven strategic goal (emphasizing organizational focus on minimizing potential loss/risk), a risk measure or both. The study demonstrated that the inclusion of risk measure(s) and/or risk-driven strategic goal(s) in PMSs allows for risk information to be incorporated in managerial decision-making and thereby results in lower risk-taking

Causal Inference in Strategic Performance Measurement Systems and Its Effect on Performance Evaluations: A Laboratory Experiment

This study aims to test the effect of explicit representation of causal relationships in strategy map component of balanced scorecards BSC on performance evaluations outcomes. To address this aim, a 2 × 2 factorial design laboratory experiment was conducted, where the inclusion of graphical information supporting causal relationships between objectives in strategy maps, and performance outcome patterns (positive vs. negative) across performance measurement perspectives of BCSs were manipulated. The findings show that the observed performance evaluation scores are driven more significantly by the performance outcomes in the outer perspectives of BSCs (financial and learning & growth) than by inner perspectives (internal business processes and customer). It was also confirmed that the difference in performance evaluation scores between two identically structured BSCs with positive versus negative performance outcomes in the outer perspectives is relatively larger in the presence of the strategy map versus when the ordered strategic objective list is presented

Open process innovation: A multi-method study on the involvement of customers and consultants in public sector BPM

Following calls to enhance risk-sensitivity of second generation Operational Risk-Aware Information Systems (ORISs), this paper aims to address the lack of ontological/epistemological grounding for the concept of Operational Risk (OR). Herein, OR is regarded both as a property of a real system and as a representational phenomenon forming part of the core of ORIS in line with Weber’s (2003) view of the core of IS. The paper explores how the ontological/epistemological position of the Critical Realist philosophy of science assists in the Requirements Definition of ORISs by providing an ontology-driven representation of the heterogeneous nature of OR. The retroductive mode of logical inference enabled by Critical Realism supports the discovery of OR causal mechanisms when the historical data about operational loss events is limited. The ontological/epistemological position suggested in the paper contributes to better understanding and representation of OR, informs OR assessment in conditions of a constantly changing socio-economical environment, and so assists in the Requirements Definition of ORISs

Psychophysiological Responses to Data Visualization and Visualization Effects on Auditors’ Judgments and Audit Quality

We conduct experiments with practicing Big 4 auditors and business students in order to investigate the psychophysiological responses to Big Data visualizations and the effects of different visualization techniques on auditor judgment and ultimately audit quality. More specifically, the first experiment with students examines whether visualizations can be designed to increase the level of a users’ arousal. Such increases in arousal have the capacity to yield significant benefits to the audit profession by drawing auditors’ attention to important patterns in data and promoting the evaluation of these patterns during evidence evaluation. Results of the first experiment using cognitive pupillometry and eye gaze measurement indicate that different visualization techniques produce significant differences in the level of arousal without interfering with information evaluation efficiency. The second experiment then investigates whether visualizations that were shown to promote higher and lower levels of arousal have differential effects on auditor judgments and audit quality. In addition, the second experiment investigates whether the reliability of the data sources underlying visualizations affect auditors’ judgments. Results from the second experiment indicate that visualizations that increase arousal enhance auditors’ ability to recognize disconfirming evidence and incorporate this evidence into their decisions. That is, auditors who view visualizations of disconfirming evidence that are designed to promote arousal recommend greater reductions to management estimates of reported revenue and increase their budgeted audit hours more than auditors who view visualizations that promote less arousal. In addition, auditors who view visualizations that increase arousal are more likely to attend to the reliability of data used to create the visualizations. Overall, the experiments reveal that understanding the root causes of different visualization techniques on arousal and auditor judgment present multiple opportunities to enhance audit quality

Transferring cognitive talent across domains to reduce the disposition effect in investment.

We consider Theory of Mind (ToM), the ability to correctly predict the intentions of others. To an important degree, good ToM function requires abstraction from one's own particular circumstances. Here, we posit that such abstraction can be transferred successfully to other, non-social contexts. We consider the disposition effect, which is a pervasive cognitive bias whereby investors, including professionals, improperly take their personal trading history into account when deciding on investments. We design an intervention policy whereby we attempt to transfer good ToM function, subconsciously, to personal investment decisions. In a within-subject repeated-intervention laboratory experiment, we record how the disposition effect is reduced by a very significant 85%, but only for those with high scores on the social-cognitive dimension of ToM function. No such transfer is observed in subjects who score well only on the social-perceptual dimension of ToM function. Our findings open up a promising way to exploit cognitive talent in one domain in order to alleviate cognitive deficiencies elsewhere

The Influence of Trait Compulsivity and Impulsivity on Addictive and Compulsive Behaviors During COVID-19.

Background: The COVID-19 pandemic has resulted in high levels of psychological distress worldwide, with experts expressing concern that this could result in corresponding increases in addictive behaviors as individuals seek to cope with their distress. Further, some individuals may be at greater risk than others for developing problematic addictive behaviors during times of high stress, such as individuals with high trait impulsivity and compulsivity. Despite the potential of such knowledge to inform early detection of risk, no study to date has examined the influence of trait impulsivity and compulsivity on addictive behaviors during COVID-19. Toward this aim, the current study examined the association between impulsive and compulsive traits and problematic addictive and compulsive behaviors during the first COVID-19 lockdown in Australia. Methods: Eight hundred seventy-eight adults completed a cross-sectional online survey during the first lockdown, between late May to June 2020. Participants completed scales for addictive and compulsive behaviors for the period prior to and during lockdown for problematic eating, pornography, internet use, gambling, drinking, and obsessive-compulsive behaviors. Negative binomial regressions examined the associations between impulsivity, compulsivity, and their interaction with problematic behaviors during lockdown, controlling for age, gender, sample, psychological distress, exposure to COVID-related stressors, and pre-COVID problems. Results: Greater trait compulsivity was associated with more problematic obsessive-compulsive behaviors (p < 0.001) and less problematic drinking (p = 0.038) during lockdown. Further, trait compulsivity interacted with trait impulsivity in relation to problematic eating behaviors (p = 0.014) such that greater trait compulsivity was associated with more problems among individuals with low impulsivity only (p = 0.030). Finally, psychological distress and/or exposure to COVID-related stressors were associated with greater problems across all addictive and compulsive behaviors, as was severity of pre-COVID problems. Discussion: Trait compulsivity was associated with addictive and compulsive behaviors in different ways. Further, the finding that stress-related variables (psychological distress and COVID-related stressors) were associated with greater problems across all lockdown behaviors supports the idea that stress may facilitate, or otherwise be associated with, problematic behaviors. These findings highlight the need for interventions that enhance resilience to stress, which in turn may reduce risk for addictive and compulsive disorders

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.</p

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements