Performance Flashcards

Question

Heilman & Chen (2005) and Kidder & Park & Parks (2001) both found

Answer 1

men doing OCBs percveived more positively - women perceived as just doing their job.

Answer 2

As some minority led organizations, particularly in nonprofit contexts already struggle

Answer 3

Performance management: “continuous process of identifying, measuring, and developing the performance of individuals and teams and aligning performance with the strategic goals of the organization (Aguinis, 2013)”

Answer 4

Organizations must use their own objectives to identify relevant criteria for evaluating their own PM. Organizations must evaluate their own PM systems based on more than one criterion category. Multiple sources should be used by organizations while collecting evaluation data. Interventions meant to improve PM should utilize different levers at different levels when assessing criteria of interest. Though recognized as important in past literature, positive reactions are plausibly not as necessary to PM as once thought, especially due to equifinality.

Answer 5

Antecedents of innovation: Cultural values re: innovation Autonomy and control Transformational leadership Team Diversity Trait openness & conscientiousness Artistic/investigative interests Positive mood And - Negative mood promotes creativity when support for creativity and positive moods are present because negative mood signals a problematic state of affairs, leading individuals to systematically address the problem at hand.

Answer 6

Re: Organ (1997), among others. Campbell (1999) pointed out that the performance factors suggested by these authors can be easily integrated as subfactors into the eight-component taxonomy, forming a hierarchical description of the latent structure of performance. H

Answer 7

How the system is developed is more important than the method used. In spite of the widespread use of judgmental indices of performance, there has been a constant dissatisfaction with these measures on the part of both researcher and practitioner. The source of this dissatisfaction has been the vulnerability of these measures to both intentional and inadvertent bias. Sex of the rater does not generally affect ratings, although female raters may be more lenient. Raters usually give higher ratings to same-race ratees, although this may be moderated by the degree of contact that members of each race have with each other. Rater experience appears to positively affect the quality of performance ratings, but the mechanism or mechanisms responsible (e.g., more training or experience with the rating form, better observation skills, better knowledge of the job requirements, etc.) is not known. sex stereotype of an occupation interacts with the sex of the ratee, such that males receive more favorable evaluations than do females in traditionally masculine occupations but that no differences or smaller differences in favor of females occur in traditionally feminine occupations. Ratees tend to receive higher ratings from raters of their same race, although this may not occur in highly integrated Raters often give more favorable ratings to same-race ratees, although situational factors may moderate this effect. situations Elmore and LaPointe (1975) reported that student ratings of college instructors’ effectiveness were positively correlated with student ratings of instructor warmth. The number of response categories available to the rater should not exceed nine. There is some advantage to using behavioral anchors rather than simple numerical or adjectival anchors. This advantage is probably increased in the absence of good dimension definitions. Ratings for administrative purposes will be more lenient than those for research purposes.. Rater training has generally been shown to be effective in reducing rating errors, especially if the training is extensive and allows for rater practice. Questions still remain about the longitudinal effects of such training, There appears to be no reduction in halo error when all ratees are evaluated on one trait, then all ratees are evaluated on the next trait, and so forth

Answer 8

*Typically, job performance is conceptualized as consisting of three dimensions: in-role or task behavior, organizational citizenship behavior (OCB), and CWB) f

Answer 9

Stars r frequency is alleged to be increasing, owing in part to the decline of the manufacturing sector and the rise of the knowledge economy (Powell and Snellman, 2004). This is because knowledge-economy jobs tend to possess features (e.g., autonomy and multiplicity of production) that lend themselves to star emergence (Aguinis and O’Boyle, 2014). e, in high-complexity jobs, the top percentile of workers more than doubles the productivity of average workers (Hunter et al., 1990) This possibly indicates that stars provide multiplicative value as opposed to a simple additive model in contributing to team outcomes. Adler (1985), another renowned labor economist, contends star status is not a function, at least not directly, of any internal attribute of the person (i.e., talent). Rather, star status is bestowed purely by market response. Put differently, market response is output and vice versa. . Further supporting normality is that supervisor ratings, the most commonly used job performance assessment tool (Aguinis, 2013), tend to be normally distributed. On the surface there appears to be ample support for the “norm of normality,” but with regard to stars, two considerations are worth mentioning. First, normality should not be confused with prevalent or natural. Many things are normally distributed, but most are not. In practice, normality appears to be the exception rather than the rule (Limpert, Stahel, and Abbt, 2001), and this is not a particularly recent finding either in the natural sciences (Groth, 1914; Powers, 1936; Sinnot, 1937) or in the social sciences (Geary, 1947; Pearson, 1895). Even when limiting the scope to management and applied psychology research, normality is by no means certain. For example, in a Psychological Bulletin article, Micceri (1989) reviewed distributions of scores from 440 achievement and psychometric measures and found that everyone diverged from normality. Micceri concluded that normal curves were about as common as unicorns. ``` The second consideration regarding a Gaussian distribution of job performance is that, as previously stated, the compendium of evidence for its normality largely rests on supervisor ratings (Aguinis, 2013). Putting aside the amount of faith one can have in something where nearly half of its measurement is noise (LeBreton, Scherer, and James, 2014; Viswesvaran, Ones, and Schmidt, 1996), ``` the bigger issue is that this may be an example of reverse causality. Researchers instruct supervisors to place employees onto normal distributions (e.g., Motowidlo and Borman, 1977; Schneier, 1977), and researchers throw out any performance-evaluation items that fail to generate normal distributions (e.g., Rotundo and Sackett, 2002). Then, with circular logic, these same data are used to verify that job performance is normally distributed ``` First, as expected in a non-normal distribution, the measures of central tendency in a star distribution are always drastically different from one another. The mean is considerably larger than the median, and thus the majority of workers in the distribution are below the arithmetic mean. -The measures of central tendency are distanced from each other—the mean is much larger than the median, and the median is much larger than the mode. ``` Third, star distributions exhibit a property known as scale invariance (Eliazar and Klafter, 2007). This means that the shape of the full star distribution shown in Figure 3.2 will be retained even if zoomed in on the top quartile, top decile, or even the top percentile—highfrequency peak to the left; long tail to the right. power-law distribution. The term power is a reference to the exponential relation between one quantity (e.g., talent) and another quantity (e.g., performance and compensation). The variance is quasiinfinite, making traditional inferential statistics that rely on stable estimates of variance (e.g., ANOVA, OLS regression, and structural equation modeling) inappropriate and prone to both Type I and Type II errors (O’Boyle and Aguinis, 2012). historians typically oscillate between great-person theory and the trends-and-forces perspective. there must come a point where small increases in intelligence yield massive differences in output. ``` where does the relation between GMA and job performance take on an exponential function (i.e., a tipping point)? ``` Do certain variables interact differently with cog ability when cog ability is at sig. higher levels? it is entirely possible that weak or even nonexistent interactions observed at normal levels of GMA become quite strong when the population is limited to geniuses. For example, CEOs tend to be high in GMA (Wei and Rindermann, 2015). CEOs also tend to exhibit higher levels of narcissism and psychopathy compared with the general population (Babiak, Neumann, and Hare, 2010; Resick, Whitman, Weingarden, and Hiller, 2009). Do these maladaptive personality traits typified by grandiosity and callousness provide a competitive advantage when coupled with a high IQ. Ready, Conger, and Hill (2010) posited that high-potential stars possess such X-factors as a drive to excel, catalytic learning capability (i.e., the ability to scan for new ideas; the cognitive functioning to integrate new ideas into existing information and then translate ideas into action), enterprising spirit, Context antecedents: Collectively, these insulators and conductors can be viewed from the perspective of cumulative advantage. Cumulative advantage can help to explain why even in very efficient markets a widening gap can emerge between those with resources and those without. Sometimes referred to as the Matthew Effect (Merton, 1968) or 80-20 Rule, cumulative advantage posits that small initial advantages in wealth, skills, talent, or just plain luck will build over time to yield large differences in output and rewards. two particularly strong conductors: multiplicity of production and monopolistic productivity. Multiplicity of production is the extent to which creating additional productivity requires less effort, resources, etc. than previous productivity. a star worker is able to capitalize on his or her past popularity to generate more productivity in the future with less individual effort. When to be careful about stars growing through monopolistic productivity: Whether the conductor of star productivity is primarily through multiplicity of production or primarily through monopolistic production has sweeping implications for an organization. Consider compensation. If stars are maintaining their status in large part by siphoning off the production of non-stars (i.e., monopolistic production), then resources are being misallocated. Star production should be symbiotic, not parasitic. Consider also selection and retention. If new potential stars recognize that the old, established stars dominate production through monopolistic practices, then the new stars will seek out better opportunities—potentially with a competitor. In essence, organizations will lose their future in order to preserve their past. Productivity ceiling as a risk-factor to stardom: In an 8-hour day, the productivity ceiling is eight deals. For nonstars who may only close one or two deals a day, the paperwork is a minor constraint to their performance because their KSAs limit their production more so than the absolute ceiling. However, for a star broker closing deals at a fast rate, the one-deal-an-hour limit is considerably more detrimental. If this broker were to receive an administrative assistant to do the half-hour of paperwork, then this would double the broker’s productivity ceiling. One challenge is whether jobs consist of just one unique task, though, as most don't. -*Beck et al. (2014) argued that for most jobs, performance is multifaceted, and when performance is aggregated across these facets, the skewed individual facets will become normally distributed. the issue of facet weight. Are all job facets equally important to the overarching job performance construct? If not, which are more integral to performance? To what extent do the weights support or refute star existence? There is also a need to investigate the degree of overlap between star performers and dark stars. How much leeway do organizations give their stars, and what effect does their differential treatment have on non-stars? Bill Gates allegedly said, “A great lathe operator commands several times the wage of an average lathe operator, but a great writer of software code is worth 10,000 times the price of an average software writer” (Veksler, 2010). Google’s Senior Vice President of People Operation (i.e., Head of HR), Laszlo Bock, reflecting on Google’s compensation policy, stated: “two people doing the same work can have a hundred times difference in their impact, and in their rewards … there have been situations where one person received a stock award of $10,000, and another working in the same area received $1,000,000” (Bock, 2015: 241) how acceptable to an organization is extensive variance in pay for the same position? An issue well known in professional sports, but largely unheard of in the private sector, is that stars create the possibility, even the inevitability, that certain employees will earn more than their supervisors do. and how much is stars' star power due to their network and support structure as it is to any internal attributes? (e.g., are they still equally star powered whenw oring in a new team in a new org?) O’Boyle and Aguinis (2012) found star effects in narrow operationalizations of CWB in sports (e.g., flagrant fouls, red cards, and ejections). meta-analytic evidence also supports a highly skewed distribution of CWB, with the majority of individuals engaged in virtually no CWB, while a small minority dominates CWB engagement (Greco, O’Boyle, and Walter, 2015).

Answer 10

Despite the alleged frequency of counterproductive work behavior (CWB) in the population, most samples exhibit exceedingly low base rates. One potential explanation for this incongruence is non-response bias, which leads to range restriction in the CWB distribution. We investigated this possibility by determining if response rates within CWB research were lower than that found across management research and whether range restriction could explain reduced CWB engagement. We also examined whether range restriction attenuated CWB’s relations to other variables. Our primary findings are that reported response rates for studies containing CWB measures are substantially lower (37%) than response rates reported within the general management literature (52.7%), and that range restriction is likely present in the CWB literature resulting in low base rates and attenuated relations to CWB. In addition, tests of publication bias indicated that low response rates are less likely to be reported, and the true response rate within the CWB literature may be considerably lower.

Answer 11

The PM literature can generally be categorized into three distinct perspectives: individual-level PM, team-level PM, and organizational-level PM. Very little research has simultaneously examined multiple levels. This is problematic given that actual performance in organizations takes place at all three levels simultaneously, and perhaps more important, all three levels of performance are intertwined. Simply stated, performance criteria represent whatever aspects of performance a certain set of stakeholders have identified as critical. o Errors can be divided into three common categories ▪ Distributional errors: incorrect representations of performance distributions across employees being evaluated (can occur in rating means – severity or leniency, or variance – range restriction and central tendency) ▪ Illusory halo: correlations between ratings of two different dimensions being higher (or lower) than the correlation between the actual behaviors reflecting those dimensions. Essentially, raters are either overestimating or underestimating the relationship between dimensions ▪ Other types of errors: perceptual errors (similar-to-me or first impression Multiple measures or single composite criterion measure ▪ Multiple best if purpose is to diagnose performance issues ▪ Composite best for comparing across units that may not do the same type of work. PM useful for research, feedback, training, and evaluation, and these are all at individual level o PM also useful for organizational planning by assessing performance at individual and team levels to inform organizational strategy, strategic workforce planning, and talent management. What: Content of measurement o Based on what level your purpose is at o Task based needs individual-level data o Team based needs team-level data, etc. Authors suggest repeated measures design to capture dynamic nature of performance. Do you want day-to-day performance? If so, will getting this data interrupt the actual performance? Can you create a high-fidelity simulation to measure performance? o Do you want maximal or typical performance? o Beware that your observation itself will likely elicit maximal performance Campbell’s model limited because focuses solely on task performance and doesn’t include OCBs ▪ Contextual performance ▪ Adaptive performance Strategies for measuring individual performance ▪ Performance appraisal ● Dominant view is that supervisor-based PA systems are costly in time and money and usually only result in negative emotions with very little demonstrable value (Nickols, 2007). This is because if PA controlled by supervisor, PA will only serve supervisor’s opinions. Nickols (2007) found that PAs often accompanied by periods of reduced productivity, heightened negative emotional states such as anxiety, depression, and stress; and lowered morale and motivation. Also foster a focus on short-term goals at the sacrifice of long-term goals. Marks et al. (2001) 10 core team processes that occur throughout the performance cycle of a team: mission analysis formulation and planning, goal specification, strategy formulation, monitoring progress toward goals, systems monitoring, team monitoring and backup behavior, coordination, conflict management, motivation and confidence building, and affect management. Organizational perspective o Organizational performance: financial outcomes are of most interest (e.g. ROI, productivity, sales), but customer service and organizational learning are also important Future research in performance measurement o Distribution: globalization, how to measure performance from a distance o Diversity: how to evaluate fairly across demographic groups

Answer 12

A review of Morgeson et al. (2005) summarized benefits of 360 feedback, such as increase in information and formal feedback between employees, increase in management learning, encouragement of goal setting and skill development, a change in corporate culture, and improved managerial effectiveness

Answer 13

found that bidirectional nature of system encouraged employees to deliberately sabotage the system with deals on giving each other high ratings.

Answer 14

Team performance: while individuals are the ones behaving, teams have behavioral interactions and processes beyond those individual behaviors that must be aggregated and considered; team performance is a bottom-up emergent process, beginning with individuals and progressing towards teams (Salas et al., 2007)

Answer 15

Big Five in Teamwork: team leadership, team orientation, mutual performance monitoring, backup behavior, and adaptability. Also important are shared mental models, closed-loop communication, and mutual trust

Answer 16

change in team performance resulting from an identified cue or cue pattern, leading to effective and efficient outcomes for the entire team; developed the most comprehensive conceptualization of team adaptation

Answer 17

● Goal model (Georgopoulos & Tannenbaum, 1971): defines org effectiveness in terms of org’s achievements of its stated official goals o Directly attempts to align PM with org strategy ● System model: views organizations as open systems that work in a close relationship with the external environment, effectiveness seen as org’s ability to survive and adapt in a changing environment ● Internal process model: effectiveness is the extent to which the internal business processes of an org are smooth, orderly, continuous, predictable, and minimally conflicting ● Human relations model: person-centered, maintains employee needs as most important aspect of org effectiveness ● Political approach: uses criteria such as responsiveness, accountability, representativeness, and adherence to democratic valuesstrategy

Answer 18

▪ Financial data – but be careful not to engage in short-sighted decisions to maximize short-term return and sacrifice long-term well-being of firm Ghalayini & Noble (1996) outline limitations of financial measures o Missing link between measuring performance in financial terms and the improvement efforts needed to improve that financial performance (i.e. how to address individual and team level performance issues with org-level financial data) o Do not take into account strategy or goals of org as an entity (i.e. ignores qualitative goals such as reputation for customer service)

Answer 19

Balanced scorecard: system of combining financial and nonfinancial measures of performance in one single scorecard (Pandey, 2005) ● Kaplan & Norton (2005) found that over 60% of orgs use a scorecard Measure financial, customer (customer satisfaction, customer retention, market share, customer profitability), internal business processes (quality of business processes in org, key objectives are process improvement and suppliers’ relations), and learning and growth (innovation, creativity, capability)

Answer 20

Six Sigma ● Developed at Motorola as a response to a large loss in productivity due to a lack of quality (Raisinghani et al., 2005) ● Historically predominantly manufacturing-based, but spreading rapidly ● Relies on planned changed, team-based collaboration, a focus on performance improvement, systems perspective, and reliance on the scientific method and statistical methodology (Jeffery, 2005) ● At first was a statistical method for tracking and reducing variability in processes, but now more complex operations improvement and problem solving methodology

Answer 21

Multilevel approach to performance measurement is best! (Salas et al., 2003

Answer 22

Results indicate that higher levels of multiplicity of productivity, monopolistic productivity, job autonomy, and job complexity (i.e., conductors of cumulative advantage) are associated with a higher probability of an underlying power law distribution, whereas lower productivity ceilings (i.e., insulator of cumulative. In addition, higher levels of multiplicity of productivity, monopolistic productivity, and job autonomy were associated with a greater proportion of productivity stars (i.e., productivity distributions with heavier tails), whereas lower productivity ceilings were associated with a smaller proportion of productivity stars (i.e., productivity distributions with lighter tails). Results were the same even while controlling for past experience. Implications: Compensation pay dispersion may be seen as more acceptable and fair to employees if they are aware that the distribution has a heavy tail (i.e., a large proportion of productivity stars). Thus, it may be beneficial to share information on the shape of the productivity distribution with various organizational members. -but if no extra pay, learning about power curves may turn off stars about their pay. which types of roles you want to prioritize star performers (power distribution in both best actor and best screenwriter) Limitations: There is an empirically documented nontrivial relationship between performance defined as behavior and performance defined as results for individuals (Bommer et al., 1995) as well as for teams (e.g., Beal et al., 2003). Nevertheless, our results are not directly informative regarding the shape of the distribution when performance is not defined in terms of results. The rest below here is mostly for personal growth: The most direct analog of cumulative advantage is compound interest, something Albert Einstein is alleged to have once quipped as “the most powerful force in the universe” (Kay, 2008). Cumulative advantage is also the result of path dependent change where a specific sequence of events “creates unequal propensities for future events” (Gluckler, 2007, p. 620). Crawford (2012) argued that, ¨ over time, positive feedback from the environment (i.e., success) allows individuals to accumulate intangible resources such as knowledge and absorptive capacity, which can then be leveraged in later interactions. Note that past productivity does not necessarily need to increase KSAs for cumulative advantage to occur. For example, in American football, the best wide receiver on a team does not need to improve his speed, catching ability, or route accuracy to increase the number of receptions and touchdowns. His past results will make the quarterback more likely to pass the ball to him, which will lead to more receptions and touchdowns independent of any increased KSAs Similarly, early productivity in an academic’s career may make other high producing academics more willing to collab with her in future research. These collaborations increase the likelihood of publication not only because the quality of work itself may be better but also because the reputation of the researcher might make a journal editor more inclined to accept the paper for publication (Peters & Ceci, 1982). Multiplicity of productivity (past success helping facilitate future success: , due to increased opportunities to perform (e.g., more time to devote to research due to decreased teaching demands), positive feedback from the environment (e.g., accepted publications), and an increased network of collaborators and resources due to past successes (e.g., better access to data collection opportunities and computing equipment), *Job characteristics We focus on three such job characteristics: job autonomy and job complexity as hypothesized conductors and productivity ceiling as a hypothesized insulator. Empirically, job autonomy generally has a positive relation with productivity (Humphrey, Nahrgang, & Morgeson, 2007). Job autonomy is an especially salient conductor because it offers high-productivity individuals the flexibility and control over processes that may lead to stratification of individuals’ output levels (Kohn & Schooler, 1983). and because stars are better able to leverage available resources (Aguinis & O’Boyle, 2014) and autonomy allows stars to build stronger and larger networks, which are known to enhance success and generate extreme productivity levels (Crawford & LePine, 2013; Oliver & Liebeskind, 1998; Zucker, Darby, & Brewer, 1998) ``` One reason is that, similar to the rationale for job autonomy, job complexity introduces more variance in worker output (Gerhart, 1988; Hunter, Schmidt, & Judiesch, 1990). ``` This productivity ceiling is particularly noticeable for jobs that have a physical and/or time limit component Even different parts of a job have different productivity ceilings: Example: # of sales calls made per day vs $ made per day - If, for example, a $1,000 sale takes about the same amount of time as a $100 sale, then revenue exhibits a higher ceiling to productivity