Relative Performance Research Articles

Keeping Up with the Joneses during an Economic Crisis: The Effect of Different Types of Pay Cuts on Employee Performance

ABSTRACT Many firms implement pay cuts to reduce labor costs during organizational crises and there are different ways to distribute pay cuts among employees. We experimentally investigate how employees respond to equal-share pay cuts compared to performance-based pay cuts. We predict and find that the effect of different ways of allocating pay cuts is moderated by employees’ relative performance before the pay cuts. Compared to equal-share pay cuts, performance-based pay cuts lead to higher performance but only for employees who underperform their peers before the pay cuts. Performance-based pay cuts also result in higher team performance. Interestingly, we also find that when pay cuts are caused by an organizational crisis, low performers do not perceive it as unfair to receive a larger share of pay reduction. Our findings contribute to both literature and practice on pay reduction during organizational crises. Data availability: Data are available from the authors upon request. JEL Classifications: D91; J33; M40.

Cash versus Share Payouts in Relative Performance Plans

ABSTRACT This study examines the risk taking properties associated with incentive plans that use relative performance evaluation, with a focus on the form of payout, whether in cash or shares. By analyzing determinants and consequences of payout form choice, I find that share-based plans offer risk-averse managers weaker incentives to pursue projects with idiosyncratic risk compared with cash plans. This occurs because share plans—unlike cash plans—expose managers to systematic performance trends, as payout values are linked to stock prices. Additionally, I document that the variation in risk taking incentives depends on expected relative performance and the strength of the incentives. Overall, this study’s findings suggest that commonly used share-based relative performance plans might not always motivate managers to pursue innovative projects with high idiosyncratic risk when projects with systematic risk are available. Data Availability: All data are available from the sources identified in the text. JEL Classifications: G30; J33; J41; M12; M41.

Optimal investment based on relative performance and weighted utility

Optimal investment based on relative performance and weighted utility

P‐96: Alignment Optimization on Gen. 4.5 G for High‐framerate Ultra‐high‐resolution Ferroelectric Liquid Crystal Displays

We achieve high‐framerate (< 100 μs) high‐contrast‐ratio ferroelectric liquid crystal displays (FLCD) on Gen 4.5. Innovatively, a new polyimide (PI) that is suitable for ferroelectric liquid crystal (FLC) alignment is synthesized and tested on the production line. It replaces Nylon 6 (N6), which was the barrier to the commercialization of FLCD. Moreover, a new FLC is synthesized to match requirements in mass production. Additionally, various materials were studied to investigate the surface energy and relative performance. It is not only proof of the feasibility on the production line, but also a significant step towards the commercialization of field‐sequential‐color high‐resolution FLCDs.

An investigation into the vapour permeability and durability of natural renders on an earthen wall system

This paper describes a novel methodology for establishing the relative moisture performance of renders used to protect a novel walling system combining traditional dense cob with a low-density thermal cob. A new method of enhancing the thermal insulation of cob walls has been developed by an European Union (EU)-funded joint UK and French project called CobBauge. The external surface of traditional cob walls (comprising subsoil, fibre and water) is normally protected from driving rain by placing the walls on a short wall called a plinth, a pronounced eaves overhang and a breathable exterior render. As the low-density fibre and clay insulating layer in the CobBauge system differs from traditional cob, a method of establishing the moisture-related performance of a range of renders needed to be instituted to aid the materials selection process. A series of test panels were constructed with the thermal cob infill, faced by a number of render types. The panels were hung in an open position in a high exposure zone and the moisture content monitored using wood-block sensors, electrical resistivity and gravimetric measurements over a period of six months. The wood-block and electrical resistivity moisture measurements showed a good level of agreement with gravimetric measurements and showed a clear differentiation between the various render choices.

Unveiling the Potential of AI in Plastic Surgery Education: A Comparative Study of Leading AI Platforms' Performance on In-training Examinations.

Within the last few years, artificial intelligence (AI) chatbots have sparked fascination for their potential as an educational tool. Although it has been documented that one such chatbot, ChatGPT, is capable of performing at a moderate level on plastic surgery examinations and has the capacity to become a beneficial educational tool, the potential of other chatbots remains unexplored. To investigate the efficacy of AI chatbots in plastic surgery education, performance on the 2019-2023 Plastic Surgery In-service Training Examination (PSITE) was compared among seven popular AI platforms: ChatGPT-3.5, ChatGPT-4.0, Google Bard, Google PaLM, Microsoft Bing AI, Claude, and My AI by Snapchat. Answers were evaluated for accuracy and incorrect responses were characterized by question category and error type. ChatGPT-4.0 outperformed the other platforms, reaching accuracy rates up to 79%. On the 2023 PSITE, ChatGPT-4.0 ranked in the 95th percentile of first-year residents; however, relative performance worsened when compared with upper-level residents, with the platform ranking in the 12th percentile of sixth-year residents. The performance among other chatbots was comparable, with their average PSITE score (2019-2023) ranging from 48.6% to 57.0%. Results of our study indicate that ChatGPT-4.0 has potential as an educational tool in the field of plastic surgery; however, given their poor performance on the PSITE, the use of other chatbots should be cautioned against at this time. To our knowledge, this is the first article comparing the performance of multiple AI chatbots within the realm of plastic surgery education.

Should Small Wind Pursue Traditional Region 3 Control?

A strategy to eliminate Region 3 control for small, fixed pitch turbines and utilize an extension of Region 2 is presented. Variations in wind probability distribution, capacity factor, and percent overshoot were examined. The relative performance of different control objectives was compared based on projected annual energy production. The results indicated that the Region 2 only control objective can produce energy equivalent to that of the currently employed Region 3 control objective over a range of wind regime-turbine combinations and capacity factors. It is suggested that the additional complexity required to provide Region 3 control for small turbines may not be warranted by the energy extraction benefits, particularly when factoring in additional equipment costs.

Data-Driven Optimal Bipartite Consensus Control for Second-Order Multiagent Systems via Policy Gradient Reinforcement Learning.

This article investigates the optimal bipartite consensus control (OBCC) problem for unknown second-order discrete-time multiagent systems (MASs). First, the coopetition network is constructed to describe the cooperative and competitive relationships between agents, and the OBCC problem is proposed by the tracking error and related performance index function. Based on the distributed policy gradient reinforcement learning (RL) theory, a data-driven distributed optimal control strategy is obtained to guarantee the bipartite consensus of all agents' position and velocity states. In addition, the offline data sets ensure the learning efficiency of the system. These data sets are generated by running the system in real time. Besides, the designed algorithm is an asynchronous version, which is essential to solve the challenge caused by the computational ability difference between nodes in MASs. Then, by means of the functional analysis and Lyapunov theory, the stability of the proposed MASs and the convergence of the learning process are analyzed. Furthermore, an actor-critic structure containing two neural networks is used to implement the proposed methods. Finally, a numerical simulation shows the effectiveness and validity of the results.

Nitrogen niche partitioning between tropical legumes and grasses conditionally weakens under elevated CO2

Abstract Plant community biodiversity can be maintained, at least partially, by shifts in species interactions between facilitation and competition for resources as environmental conditions change. These interactions also drive ecosystem functioning, including productivity, and can promote over‐yielding‐ an ecosystem service prioritized in agro‐ecosystems, such as pastures, that occurs when multiple species together are more productive than the component species alone. Importantly, species interactions that can result in over‐yielding may shift in response to rising CO2 concentrations and changes in resource availability, and the consequences these shifts have on production is uncertain especially in the context of tropical mixed‐species grasslands. We examined the relative performance of two species pairs of tropical pasture grasses and legumes growing in monoculture and mixtures in a glasshouse experiment manipulating CO2. We investigated how over‐yielding can arise from nitrogen (N) niche partitioning and biotic facilitation using stable isotopes to differentiate soil N from biological N fixation (BNF) within N acquisition into above‐ground biomass for these two‐species mixtures. We found that N niche partitioning in species‐level use of soil N versus BNF drove species interactions in mixtures. Importantly partitioning and overyielding were generally reduced under elevated CO2. However, this finding was mixture‐dependent based on biomass of dominant species in mixtures and the strength of selection effects for the dominant species. This study demonstrates that rising atmospheric CO2 may alter niche partitioning between co‐occurring species, with negative implications for the over‐yielding benefits predicted for legume‐grass mixtures in working landscapes with tropical species. Furthermore, these changes in inter‐species interactions may have consequences for grassland composition that are not yet considered in larger‐scale projections for impacts of climate change and species distributions. Read the free Plain Language Summary for this article on the Journal blog.

Abilities analysis of problem-solving process awareness for elementary school students with different problem-solving performances

Background: Awareness is core ability in problem-solving process, but related performance analysis of problem-solving process awareness for elementary school students is still under study. It is one of the research gaps. This research summarizes problem-solving process awareness dimensions of translation and implementation to study. Former includes recognition and representation, and latter includes strategy and execution, review and check. Objective: According to the results of the literature analysis and research gap, this study aims to explore the problem-solving process awareness ability for elementary school students with different problem-solving performances by utilizing related instruments. Method: This research utilized two instruments of problem-solving process awareness and problem-solving to assess process awareness and problem-solving performances each for elementary school students. There were 389 elementary school students in Chiayi of Taiwan were selected by using stratified and cluster sampling to collect and analyze data. The single-factor multivariate mean test and η 2 effect size value, Roy-Bargman step-down F test and simultaneous confidence interval test were carried out. The analysis above which was conducted by SPSS for Windows. Result and conclusion: It is found that there were significant differences in performances of problem-solving process awareness for students with different problem-solving abilities after adequate data analysis. The performances are considerably different in translation and implementation awareness for students with differing word problem solving ability that translation awareness included recognition and representation awareness, and implementation awareness included strategy and execution, review and check awareness. So, conclusion is listed as follows. It is that students with different problem-solving performances have real differences in translation, implementation and overall awareness of problem-solving process corresponding to research problem.

Beyond apples and oranges: unraveling the complexity in corporate sustainability reporting

PurposeThis investigation highlights the discrepancies in sustainability reporting practices, and their implications for sustainable service.Design/methodology/approachA comparative analysis methodology was employed, examining sustainability reports from similarly situated companies, specifically PepsiCo and Coca-Cola and The Home Depot, Lowe’s and HomePro. This approach was chosen to uncover variances in sustainability reporting and practices within these sectors using the Sustainability Accounting Standards Board (SASB) guidelines which all four firms followed in their sustainability reports.FindingsThe study reveals significant disparities in how companies within the same industry apply SASB guidelines. These inconsistencies highlight a broader issue of non-standardization in sustainability reporting, leading to challenges in effectively evaluating the relative performance of companies in the same sector.Practical implicationsThe findings suggest managers must prioritize standardized and transparent sustainability reporting to build stakeholder acceptance and trust.Originality/valueThis paper contributes to the existing literature by providing a detailed comparison of sustainability practices in two distinct industry sectors. It offers new insights into the challenges and importance of standardizing sustainability reporting and the potential impact on stakeholders.

Profitable environmental corporate social responsibility under managers’ relative profit performance competition

AbstractWhen managers face relative profit performance competition, we formulate a green managerial delegation contract where the owners impose profit‐oriented environmental corporate social responsibility (ECSR) on their managers. We show that the owner adopts ECSR as a commitment device to reduce outputs under quantity competition if the degree of relative profit performance competition is sufficiently high, which can increase not only industry profits but also environmental quality. We also examine an endogenous choice of ECSR and find that the profitable level of ECSR in the asymmetric ECSR case is higher than that in the symmetric ECSR case while both firms undertake ECSR in equilibrium if the severity of competition is sufficiently high.

Double managerial delegation contracts with relative profit performance and environmental performance incentives under emission taxes

AbstractThis paper examines the strategic relations between emission taxes and firms' managerial delegation contracts, which include incentives based on relative profit performance (RPP) and environmental performance (EP). We demonstrate that under quantity (price) competition, the government imposes higher (lower) emission taxes, while the firm owner sets lower (higher) EP incentives and negative (positive) RPP incentives, which leads to lower (higher) welfare. We also explore an endogenous competition mode game and find that quantity (price) competition emerges when both consumers' green willingness‐to‐pay (WTP) and product differentiation are low (high). Our findings suggest that public education on greenness is crucial for enhancing EP incentives in the design of managerial delegation contracts, while intense product market competition may be detrimental to consumers and society, especially when consumers' green WTP is low.

Comparing prospectively assigned trial and real-world lung cancer patients.

Aim: To evaluate the comparability of a probable clinical trial (CT) cohort derived from electronic medical records (EMR) data with a real-world cohort treated with the same therapy and identified using the same inclusion and exclusion criteria to emulate an external control. Methods: We utilized de-identified patient-level structured data sourced from EMRs. We then compared patterns of overall survival (OS) between probable CT patients with those drawn from non-contemporaneous real-world data (RWD) using a two-sided log-rank test, hazard ratios (HRs) using a Cox proportional-hazards model and Kaplan-Meier (KM) survival curves. Each regression estimate was calculated with a corresponding 95% confidence interval. We additionally conducted multiple matching methods to assess their relative performance. Results: Median (standard deviation) OS was 10.2 (0.7) months for the RWD arm and 11.3 (1.3) for the probable CT arm with a Log rank p-value equal to 0.4771. OS in both cohorts is longer than the reported CT median OS of 9.2 (0.6). The HRs generated under all five assessed matching methods (including without adjustment) were not statistically significant at the 95% confidence level. Conclusion: Our results suggest, with caveats noted, that survival patterns between real-world and CT cohorts in this NSCLC setting are not statistically significantly different.

Earn More Tomorrow: Overconfidence, Income Expectations, and Consumer Indebtedness

AbstractThis paper examines whether biased income expectations due to overconfidence lead to higher levels of debt taking. We show suggestive evidence for a link between overconfidence and borrowing behavior in a representative survey of German households (German Socio‐Economic Panel–Innovation Sample [GSOEP‐IS]). This motivates a laboratory experiment to study causality behind these effects. In two experiments, participants can purchase goods by borrowing against their future income. We exogenously manipulate overconfidence about income expectations by letting income depend on relative performance in hard and easy quiz tasks. In the main experiment, we successfully generate biased income expectations and show that participants with higher income expectations initially borrow more. Overconfident participants scale back their consumption after income feedback. However, they remain in higher debt at the end of the experiment, which has real financial consequences. In a robustness experiment, we rule out that overborrowing is driven by low prices of goods. Even though the expected income manipulation works less well in this experiment, debt‐taking behavior is very similar and correlates with income expectations and overconfidence.

Relative Phenotypic Performance of Crossbred Chicken as Step in Synthetic Breed Development in Ethiopia: A Review Article

The present review article aims to provide and summarize synthesized information regarding some of economically important traits on reproductive and productive performance of crossbred chicken to develop both adaptive and sustainable breed to the intended beneficiaries. Most of crossing were used full diallel mating design in both direct and reciprocal ways. Growth traits, egg production traits, reproductive traits and other economically important traits of crossbred chicken were assessed in comparison to their counterpart’s purebred both native and exotic parents. In the majority of crossbreeding studies, the hybrids surpassed the original native parental breeds in various traits studied, including body weight, feed conversion ratio, age at first egg, egg production, egg weight, and egg mass. The majority of hybrids achieved sexual maturity at an earlier age, laid more eggs, and produced a greater egg mass when compared to local chickens. Eggs from the hybrids were also heavier than those from the local chickens in certain crossbreeding experiments. In overall, crossbred chickens that combine the blood of exotic and local breeds tend to perform relatively better than indigenous chickens, which are typically characterized in low production due genetics. The frequent production of F<sub>1 </sub>crossbred demands in subsequent importation of exotic parent due to produced offspring chicken are terminal genetically. Also, the degree of heterosis retained in the crossbred decreased as generation increased due recombinant ad segregations effects. To overcome such problem producing adaptive and sustainable chicken breed through synthetic breeding is crucial for developing countries like Ethiopia.

Combined selection for productivity, adaptability, and stability in corn genotypes for baby corn production

AbstractBaby corn is the name given to the female inflorescence of corn (Zea mays L.) before fertilization, being harvested in 2–3 days after the issuance of the styles‐stigmata. Currently, in Brazil, there is no specific corn cultivar for baby corn production, which leads to the use of popcorn and sweet corn cultivars because they are more accepted in the food industry. Therefore, the objective of this work was to estimate the genetic parameters and determine the efficiency of simultaneous selection based on productivity, adaptability, and stability of corn genotypes for baby corn production in the state of Espírito Santo, Brazil. The evaluations were conducted in 2019 on family properties in six municipalities in the state of Espírito Santo. Eleven corn genotypes were evaluated for baby corn production, being a double hybrid, four native varieties, and six commercial varieties. The design was randomized blocks with four repetitions each. The genetic parameters were estimated, which were obtained using the best linear unbiased prediction (BLUP), and the selection was carried out by the harmonic mean of the relative performance of genotypic values (HMRPGV). It was observed that the environments influenced the performance of the genotypes, configuring specific adaptation. The genotypes AG 1051, Aliança, and BR 106 presented the best performances in all the environments evaluated, considering, simultaneously, the productivity, adaptability, and stability of marketable ears. The HMRPGV method provided optimized selection of corn genotypes to produce baby corn with high productive potential, predictable behavior, and responsive to environmental stimuli.

Temporal Course of Interference Control from Early to Late Young Adulthood: An ERP Study.

In the present study, we aimed to investigate the neural dynamics of interference control using event-related potentials (ERPs) to reveal time course of interference control from the beginning to the end of young adulthood. Three groups of participants aged 19-21, 23-27 and 28-44 performed a Stroop task. The results revealed age differences in both accuracy and ERP amplitudes during all aspects of interreference control processing that reflect selective attention (P2), conflict monitoring (N2), conflict evaluation (P3) and interference control (N450). Both younger groups made more errors on incongruent trials compared to participants in their early 30s. The presence of higher P2 and N2 amplitudes, diminished P3 and again higher N450 amplitudes in participants in their early 20s points to a shortage of available resources for top-down control at this age. These results are in accordance with structural and functional studies that show that development of the frontoparietal network, which underlies interference control, continues after adolescence. While brain mechanisms are still developing, the use of accompanying cognitive abilities is still not optimal. The findings that change in neural dynamics and related performance continues into early adulthood challenge current models of cognitive development and call for new directions in developmental theorizing.

Ozone, nitrogen dioxide, and PM2.5 estimation from observation-model machine learning fusion over S. Korea: Influence of observation density, chemical transport model resolution, and geostationary remotely sensed AOD

High-resolution multi-component estimates of ground-level air pollutants are necessary for assessing their impacts to human health, agriculture, and ecosystems. We demonstrate a high-resolution fusion and downscaling approach over South Korea for May 2016 and May 2021. Daily 1 km fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) concentrations are calculated at ground level using a random forest machine learning (ML) algorithm, with predictors including reanalysis meteorology, satellite aerosol optical depth (AOD), and gridded surface fields from chemical transport models (CTM). The ML model is tested for May 2016, coinciding with the Korea-United States Air Quality Study (KORUS-AQ) intensive field campaign, and for May 2021, to allow incorporation of observations from the Geostationary Environment Monitoring Spectrometer (GEMS). In the tests for May 2016, the correlation coefficients (R) and root mean squared errors (RMSE) relative to withheld observations of daily-averaged pollutants in 10-fold cross-validation are promising: 0.93 (5.5 μg/m3), 0.90 (5.5 ppbv), and 0.95 (4.7 ppbv) for PM2.5, O3, and NO2, respectively. Relative performance is assessed for alternate choices of predictors: (a) 80-km global reanalysis Copernicus Atmosphere Monitoring Service (CAMS) vs. 4-km regional Weather Research and Forecasting model coupled with Chemistry (WRF-Chem); (b) AOD polar-orbiting Moderate Resolution Image Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) vs. geostationary GEMS; and (c) variations in surface observation density. This study is among the very first to incorporate both CTM and GEMS AOD for building surface high resolution multiple air pollution predictions over South Korea.

Intercomparison of flux-, gradient-, and variance-based optical turbulence (C n2) parameterizations

For free-space optical communication or ground-based optical astronomy, ample data of optical turbulence strength (C n 2) are imperative but typically scarce. Turbulence conditions are strongly site dependent, so their accurate quantification requires in situ measurements or numerical weather simulations. If C n 2 is not measured directly (e.g., with a scintillometer), C n 2 parameterizations must be utilized to estimate it from meteorological observations or model output. Even though various parameterizations exist in the literature, their relative performance is unknown. We fill this knowledge gap by performing a systematic three-way comparison of a flux-, gradient-, and variance-based parameterization. Each parameterization is applied to both observed and simulated meteorological variables, and the resulting C n 2 estimates are compared against observed C n 2 from two scintillometers. The variance-based parameterization yields the overall best performance, and unlike other approaches, its application is not limited to the lowest part of the atmospheric boundary layer (i.e. the surface layer). We also show that C n 2 estimated from the output of the Weather Research and Forecasting model aligns well with observations, highlighting the value of mesoscale models for optical turbulence modeling.