Bias In Performance Evaluation Research Articles

Stochastic optimization of solar-based distributed energy system: An error-based scenario with a day-ahead and real-time dynamic scheduling approach

Distributed energy systems (DES) have garnered global attention as a promising solution for the expansion of renewable energy sources. However, stochastic uncertainty in renewable sources poses significant challenges in the collaboration optimization of system design and operation. In this study, a comparison analysis was conducted to assess the effectiveness of the conventional distribution-based scenario generation (DS) method for stochastic optimization of a distributed energy system in residential buildings. The results revealed that the DS method inaccurately captured extreme scenarios and exhibited limitations in operation optimization, leading to significant performance evaluation bias. To address these challenges, a novel stochastic optimization approach was developed based on error-based scenarios and a day-ahead and real-time dynamic scheduling strategy (ES-DRS). This approach incorporated solar energy prediction errors to more accurately characterize extreme scenarios, while also considering dynamic dual-scale meteorological boundary condition for rolling operation optimization. Furthermore, the buffer storage and coverage periods in ES-DRS were investigated and discussed during dynamic scheduling. Results demonstrated that when the buffer storage and coverage period were set at 36.22 kWh in summer and 24 h, respectively, the DES with ES-DRS achieved optimal multi-objective performance. This resulted in an annual total cost of 3.21 × 104 USD and CO2 emission of 5.82 tons, representing reductions of 26.45% and 61.06%, respectively, compared to the conventional strategy. Overall, this research contributes to advancing uncertainty analysis and scenario-based optimization in DES, highlighting the potential benefits of adopting the ES-DRS approach to maximize overall performance from both economic and environmental perspectives.

A Review of Performance Management in State-owned Enterprises and Private Enterprises in China

In order to improve profits, the theory of enterprise performance management has formed a corresponding theoretical framework and system. Enterprises can improve performance management methods based on their own situation. This research compares the differences between state-owned enterprises and private enterprises through literature review. The existing papers mainly focus on performance feedback and communication mechanisms, the application of performance management and corporate strategy, and the enthusiasm of employees to participate in performance management. The existing papers mainly focus on performance feedback and communication mechanisms, the application of performance management in line with company strategies, and the initiative of employees to participate in performance management. Neglecting the specific role of state-owned enterprises and not combining performance management with their social responsibility. In addition, the imperfect performance indicator system has also led to the problem of not being greatly influenced by subjective factors within the enterprise. The accuracy of performance evaluation in many enterprises is often influenced by human factors. The design of performance management evaluation indicators is not scientific, the evaluation is unfair, the concept of human resource management is lack of correctness, strategic planning, single evaluation results, ineffective use, lack of follow-up, and frequent communication in performance management; The recruitment and allocation of personnel are unreasonable, the construction of the management system is highly arbitrary, and there is a significant subjective bias in performance evaluation.

Potential in-group bias at work: Evidence from performance evaluations

This paper investigates the existence of in-group bias (preferential treatment of one’s own group) in performance evaluations. Drawing information from an educational setting and employing a unique dataset, we use principals’ observational assessment of teachers to examine the impact of gender interactions on evaluation of employees. Our results indicate that average classroom observation ratings for female teachers, relative to males, were 0.19 of a standard deviation higher when they were evaluated by female principals. We explore the mechanisms and present convincing sets of results consistent with the tendency of superiors to favor same-gender subordinates. Several robustness checks and different placebo tests support our findings.

Perceptions of Managerial Bias in Performance Evaluations: How Employee- Manager Demographics Influence Employee Bias Perceptions

Perceptions of Managerial Bias in Performance Evaluations: How Employee- Manager Demographics Influence Employee Bias Perceptions

Gender Bias in Performance Evaluations: Evidence from a Field Experiment

Gender Bias in Performance Evaluations: Evidence from a Field Experiment

Incentivising accuracy reduces bias in the imposter phenomenon

The imposter phenomenon (IP) involves a bias towards negative performance evaluation. While dispositional theories predict that such biases are inflexible, situational theories suggest that they may respond to accuracy incentives. In this study, we tested whether performance evaluation bias in IP is responsive to financially incentivising accuracy. Participants (n = 225) high and low in IP solved a set of reasoning problems that they were informed were designed to test their intelligence. After the task, participants estimated their performance, in either an incentivised or unincentivized condition. The results replicated previous findings, as participants high in IP evaluated their performance more negatively. However, when incentivised to do so, high IP participants became more positive in their self-assessments. Amongst low IP participants, no effect of incentive was revealed. These findings emphasise the importance of situational factors in understanding and intervening on the biases associated with IP.

Exploring the nexus between microlevel and contextual influencers on women leaders’ paradox mindset

PurposeWomen leaders struggle with the persistent paradoxical expectations. Literature suggests that a paradox mindset helps to leverage these tensions. This study aims to understand the nexus between the microfoundations of individual women leaders’ experiences, their responses and the organisational context, which enables or hinders their paradox mindset.Design/methodology/approachThis study adopted a qualitative approach by conducting semistructured interviews with 14 women, all senior leaders in corporate South Africa.FindingsThe results reveal the interaction in the nexus between, firstly, women leaders’ authenticity and awareness as key anchors that enable them to adopt a paradox mindset and, secondly, the organisation’s role in creating hindrances or opportunities to leverage tensions. Women leaders in our sample applied one of two strategies: they either adapted to the environment or curated a subenvironment. This study shows that, if done authentically, through her own agency, a woman can influence interactions that make it easier to manage tensions within her environment, especially those created by negative performance evaluation because of unconscious institutional gender bias.Research limitations/implicationsThe extent to which the findings of this research can be generalised is constrained by the selected research context.Originality/valueThis research contributes to the literature on paradox theory by revealing organisational contextual influencers, such as institutional bias in negative performance evaluation, which hinders a woman leader’s opportunity to be hired or promoted. These organisational influences also interact with women leaders’ ability to embrace paradox and internally leverage agentic and communal tensions.

How centrality bias in subjective evaluation affects positive and negative employee work behavior: a real-effort task experiment

PurposeBased on the referent cognitions theory (RCT), individuals compare their outcomes to a given reference point. The purpose of this study is to investigate the effect of centrality bias in subjective performance evaluation on two employees’ work behaviors; willingness to exert work effort and retaliation intention.MethodsA 2 × 2 × 2 between-subject real-effort task experiment was conducted on 162 Accounting and Management students. Centrality bias and level of task difficulty were each manipulated into two groups. Meanwhile, the level of performance was divided based on the average score of the real-effort task.FindingsThe experimental data were examined using MANOVA and PROCESS macro regression. It reveals that centrality bias negatively affects willingness to exert work effort through perceived procedural fairness and positively affects retaliation intention. These findings align with the RCT in explaining the perceived procedural fairness psychological mechanism and the work behavior resulting from an unfair evaluation procedure.Originality/valueThis study is the first of its kind to investigate the effect of centrality bias in subjective performance evaluation on positive and negative employee behaviors concurrently, which refers to the real-effort experimental task. The study demonstrates the significant impact of centrality bias on unwillingness to exert effort and adverse behavior.

Social watching the 2020 presidential and vice-presidential debates: the effect of ideological homogeneity and partisan identity strength

This study presents a novel test of the effects of social watching a live campaign debate. We recruited just over 500 participants to view one of the two 2020 presidential campaign debates or the vice-presidential debate in real time via Zoom watch rooms. We experimentally manipulated the social dynamics of these Zoom watches to include either ideologically homogenous real-time chat, heterogenous chat, or no chat. We found asymmetry in the extent to which these chat manipulations exacerbated biased information processing. Participants in the homogenous chat Zoom sessions were more likely to provide negative debate performance evaluations of the out-group candidate but were no more likely to provide positive evaluations of the in-group candidate. Stronger partisans exhibited more bias in performance evaluation regardless of chat condition but, contrary to our expectations, did not engage in more chat compared to weak partisans.

Gender bias in performance evaluations: The impact of gender quotas

The intention behind imposing quotas for women on corporate boards is to close the gender gap in economic participation and help women to be promoted within organizations. However, the broader social psychological literature lends support to ideas that affirmative action policies, such as quotas, may do more harm than good for the beneficiaries. We extend this idea beyond the affected beneficiaries and ask whether this unintended negative effect spills over to women who are not immediate targets of the quota, by signaling incompetence. We develop an experimental design to investigate whether the announcement (study 1) and the implementation (study 2) of a quota for women have a direct negative effect on performance evaluations and hence reinforce the existing gender bias in evaluation. We observed that the performance of women was evaluated significantly lower than that of men. However, this gender bias was limited to sequential (rating) evaluations and was not evident in joint (ranking) evaluations. The quota did not significantly influence the amount of this bias. In addition, we observed more pronounced sexism in males compared to females. Results of study 2 gave a hint to an association between higher sexism and lower evaluations of women’s performance. We also found some evidence for a stronger evaluation bias in females when controlling for sexist attitudes. Hence, our results imply that the bias, which is overall quite robust and strongly pronounced, is still affected by individual gender-related characteristics.

Ethnic/Racial Bias in Medical School Performance Evaluation of General Surgery Residency Applicants

Differential use of communal terms (caring/unselfish traits) versus agentic terms (goal-oriented/leadership/achievement traits) may reveal bias and has been extensively reported in letters of recommendation for residency. We evaluated bias in medical student performance evaluations (MSPE) of general surgery residency applicants. This is a retrospective study evaluating ethnic/race bias, as measured by differential use of agentic and communal terms, in MSPEs of residency applicants. 50% of MSPEs were randomly selected. An ethnic bias calculator derived from an open-source online gender bias calculator was populated with a list of validated agentic and communal terms. Relative frequency of communal and agentic terms was used to estimate bias. Multivariable regression was used to assess the association between the terms and ethnicity/race. US medical students applying for a categorical surgery residency position at a single academic institution for a single Match cycle. A total of 339 MSPEs were reviewed from 119 US medical schools. Genders were equally represented (women, 51.6%); most participants were white and Asian applicants (79.1%). Overall, MSPEs were more agency biased (65.2%) than communal biased (16.2%) or neutral (18.6%). MSPEs for Black and Hispanic/Latinx applicants were more likely to contain communal rather than agentic terms (adjusted OR: 3.02, 95% CI: 1.52-6.02) when compared to white and Asian applicants. This finding was independent of MSPE writer's gender or rank. Surgery residency applicants self-identifying as Black and Hispanic/Latinx were more likely to be described using communal traits compared to white and Asian applicants, suggesting ethnic/racial bias. Such differences in language utilized in MSPEs may impact residency opportunities for applicants who are under-represented in medicine. Educational efforts aimed at MSPE writers may help to reduce bias.

Resource Similarity, Market Commonality, and Spatial Distribution of Hotel Competitive Sets

Index scores and competitive sets (compsets) play a critical role in the performance and evaluation of hotels. The reliance on these metrics has drawn skepticism in recent years as competitive sets may be opportunistically chosen, creating bias in performance evaluation. Drawing from the principal–agent theory and the theory of incentives, we explore whether the distance of the competitors chosen for a hotel’s compset influences revenue per available room (RevPAR) index scores. Based on the concepts of resource similarity and market commonality, we develop a novel mathematical model through which we empirically analyze a large dataset of 10,000 compsets. We find evidence that competitor distance influences index performance and that this relationship is bidirectional. Results show that hotels that outperform the competition may use distance to inflate RevPAR indices, while those that underperform may use distance to further reduce scores. These conflicting results may be reflected from the reverse motivations of the stakeholders.

Performance Information, Racial Bias, and Citizen Evaluations of Government: Evidence from Two Studies

AbstractSocial accountability reforms emphasize expanding performance information disclosure and incorporating citizen feedback into performance evaluations of public organizations. However, social accountability scholarship has largely ignored possible discriminatory implications of performance information use despite calls for more social equity research. We look to bridge these two literatures, arguing that increasing exposure to performance information can actually activate racial bias in citizen feedback. Using two samples of White MTurk participants residing in the United States, we test this argument in a Negative Performance Information Study (n = 800) and a Positive Performance Information Study (n = 800). In the Negative Performance Information Study, we find increased exposure to negative performance information triggers more negative performance evaluations of public organizations led by Black public managers, but not White public managers, and strengthens preferences to fire Black public managers, but not White public managers. In the Positive Performance Information Study, we find increased exposure to positive performance information has no impact on performance evaluations of Black, nor White public managers but strengthens preferences to reappoint White, but not Black public managers. These findings suggest increasing exposure to performance information triggers racial bias in performance evaluations and preferences for holding public managers accountable.

Ethnic/Racial Bias in Medical Student Performance Evaluations of General Surgery Residency Applicants

Ethnic/Racial Bias in Medical Student Performance Evaluations of General Surgery Residency Applicants

Nationalistic bias in sport performance evaluations: An example from the ski jumping world cup

Illegitimate biases of non-independent judges represent a threat to the legitimacy of international sport competitions. Judges’ nationalities represent one source of bias, as they consciously or subconsciously may prefer athletes from their own nation. Such biases may affect the outcomes of competitions. The literature offers no complete consensus on the magnitude, origin and stability of such biases. In this paper, we shed light on these problems, using international ski jumping as an example. We draw on data from the FIS World Cup competitions in the 2006–2008 and 2015–2016 seasons and estimate a series of fixed-effects models to test hypotheses on nationalistic biases. Our results reaffirm suspicions of nationalistic bias in major ski jumping competitions, but also show their magnitude is too little to be of major relevance to competition outcomes. The biases vary between nations, but do not change markedly over the study period. Abbreviation: FIS: Federation International de Ski.

Likeability in subjective performance evaluations: does it bias managers’ weighting of performance measures?

In this paper, we investigate how subordinate likeability induces bias in managers’ subjective performance evaluations. Based on the affect-consistency heuristic, we expect managers who use multiple performance measures to subjectively evaluate their subordinates’ performance to place greater weight on likeability-consistent performance measures than on likeability-inconsistent measures. Hence, we predict that likeability and performance information interact in affecting managers’ performance evaluations. The results of our experiment support this prediction. In line with prior research, we find evidence of likeability bias in subjective performance evaluations: likeable subordinates receive more favorable evaluations than dislikeable ones. We further find that participants adjust their performance evaluations in the presence of likeability-consistent performance information to a greater extent than in the presence of likeability-inconsistent performance information. Thus, in accordance with the affect-consistency heuristic, our results indicate that likeability bias occurs due to a differential, biased weighting of performance measures. Additionally, we find that perceived likeability is also affected by subordinates’ performance, which in turn partially mediates the effect of subordinate performance on evaluations: good performers are more likeable than poor performers. Hence, this can exacerbate likeability bias. We discuss the implications of our findings for the design of performance evaluation systems in practice.

Evaluator Bias in Performance Evaluation of Online Transportation Driver: Empirical Study in Indonesia

Online transportation as a developing industry in Indonesia applies bonus-or-terminate incentives based on both objective and subjective performance evaluation. Regarding bias problems often found in the subjective evaluation, this paper aims to examine factors that influence bias in performance evaluation of the online transportation drivers. The data were collected by an online survey to users of online transportation in Indonesia using convenience sampling. Multiple regression analysis was utilized to analyze 163 data. The result shows that users of online transportation services tend to generate a biased rating, which is leniency bias. Altruism and knowledge of incentives scheme as the users’ internal factors significantly affect the biased evaluation. On the other hand, the external factors of the users, i.e., the frequency of usage and evaluation timing, do not significantly affect the biased evaluation. However, the other external factor, i.e., travel distance and duration, is found to affect the leniency bias positively. This paper concludes that more information related to the evaluation object and the inherent characteristic of an individual as the effect of collectivist national culture may lead to the generation of biased performance evaluation by the evaluator to help evaluated party avoiding penalty/termination in this competitive working environment.

How Calibration Committees Can Mitigate Performance Evaluation Bias: An Analysis of Implicit Incentives

ABSTRACTWhile prior research on performance evaluation bias has mainly focused on the determinants and consequences of rating errors, we investigate how a firm can provide implicit incentives to supervisors to mitigate these errors via its calibration committee. We empirically examine the extent to which a calibration committee incorporates supervisors' evaluation behavior with respect to their subordinates in the performance evaluation outcomes, i.e., performance ratings and promotion decisions, for these supervisors. In our study, we distinguish between lack of skills and opportunism as two important facets of evaluation behavior, which we expect the calibration committee to address differently. Using panel data of a professional service firm, we show that supervisors' opportunistic behavior to strategically inflate subordinates' performance ratings is disciplined through a decrease in the supervisors' own performance rating, while the supervisors' skills to provide less compressed and, thus, more informative performance ratings is rewarded through a higher likelihood of promotion.

The Effects of Accountability on Likeability Bias in Subjective Performance Evaluations: An Eye-Tracking Study

This study uses an eye-tracking experiment to investigate the effects of accountability on favoritism in subjective performance evaluations. While prior work provides evidence that managers exert favoritism when subjectively evaluating the performance of preferred subordinates, less is known about how managers use their discretion and deal with performance information when exerting favoritism as well as possible control mechanisms firms may implement to mitigate its occurrence. We develop and test theory suggesting that the effectiveness of accountability to mitigate favoritism depends on managers’ cognitive processing of performance information. We argue that accountability will cause managers to examine performance information more thoroughly, which may entail having to scrutinize information which reflects unfavorable on a preferred subordinate. This causes cognitive dissonance and managers resolve this dissonance by engaging in motivated reasoning and cognitively discounting this information. The more managers reduce cognitive dissonance by discounting unfavorable information, the less is the favoritism-mitigating effect of accountability. Consistent with our prediction, we find that the more cognitive processing managers allocate to information that reflects unfavorable on a preferred subordinate, the lower the efficacy of accountability in mitigating favoritism. We contribute by enhancing our understanding of the effects of accountability in subjective performance evaluation.

Individual and job-related determinants of bias in performance appraisal: The case of middle management in health care organizations.

Accountable care has changed organizational models adopted by health care organizations profoundly and, consequently, the skill set required for doctor-managers who have become middle managers and must deal with the operational management of their units. Doctor-managers must carry out clinical tasks as well as tasks related to budgeting, goal setting, and performance evaluation. The performance evaluation bias, defined as the misalignment between a ward unit's objective performance (as assessed by technical bodies or agencies) and self-assessed performance by the head of the unit, may have serious consequences for individuals and organizations. The aim of this study was to identify determinants of performance appraisal bias based on the mismatch between self-reported and official performance data. Specifically, we analyzed the role played by managerial behavior, training, engagement, and perceived organizational support at the individual level, as well as the particular unit's task diversity, complexity, and predictability. We collected primary and secondary data referable to a population of ward unit heads in the Italian National Health Service. A linear regression model predicting performance appraisal bias was employed. High levels of engagement and perceived organizational support were associated with reduced performance appraisal bias, whereas high levels of predictability and task diversity were associated with increased degree of error. Doctor-managers attending training programs in health care management and ward unit task complexity did not affect bias significantly. Policy makers and hospital managers should provide heads of units with tools that enable them to conduct ongoing monitoring and accurate appraisal of performance. Doctor-manager performance appraisal bias may be diminished by a perception of having support of the organization and direct superiors. Training programs can be revised to incorporate performance appraisal, and good performance may be incentivized with rewards.