PSY8711 Principle of Industrial/Organizational Psychology

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PSY8711 Principle of Industrial/Organizational Psychology


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  • Describe performance appraisal and performance management.
  • Compare and contrast the two approaches. Identify the strengths and weaknesses of each.
  • Does a forced distribution appraisal system lead to increased organizational performance?
  • What has been your experience with these approaches?

Journal of Applied Psychology 2017, Vol. 102, No. 3, 421– 433 © 2017 American Psychological Association 0021-9010/17/$12.00 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Performance Appraisal and Performance Management: 100 Years of Progress? Angelo S. DeNisi Kevin R. Murphy Tulane University University of Limerick We review 100 years of research on performance appraisal and performance management, highlighting the articles published in JAP, but including significant work from other journals as well. We discuss trends in eight substantive areas: (1) scale formats, (2) criteria for evaluating ratings, (3) training, (4) reactions to appraisal, (5) purpose of rating, (6) rating sources, (7) demographic differences in ratings, and (8) cognitive processes, and discuss what we have learned from research in each area. We also focus on trends during the heyday of performance appraisal research in JAP (1970-2000), noting which were more productive and which potentially hampered progress. Our overall conclusion is that JAP’s role in this literature has not been to propose models and new ideas, but has been primarily to test ideas and models proposed elsewhere. Nonetheless, we conclude that the papers published in JAP made important contribution to the filed by addressing many of the critical questions raised by others. We also suggest several areas for future research, especially research focusing on performance management. Keywords: performance, criteria, ratings, appraisal, evaluation Supplemental materials: articles are concerned with the type of performance appraisal more commonly done in organizations. Our review will focus on the issues associated with the two processes and how they have developed over the years. We will pay special attention to the role that the Journal of Applied Psychology (JAP) has played in this history, noting when articles in the journal have made real contributions and when the journal has had less impact. Space limitations make it impossible to describe all of the important articles that contributed to the body of research in performance appraisal and performance management, but the supplemental material for this issue of JAP includes more information on articles that had the greatest impact in each area (regardless of where they were published) as well as a bibliography of relevant articles in JAP over the last 100 years. The assessment of people’s performance at work—performance appraisal— has been of interest to scholars and practitioners for literally hundreds of years. More recently, there has also been a growing interest in the process of managing performance. The two topics are clearly related, but they are not identical. Performance appraisal refers to a formal process, which occurs infrequently, by which employees are evaluated by some judge (typically a supervisor) who assesses the employee’s performance along a given set of dimensions, assigns a score to that assessment, and then usually informs the employee of his or her formal rating. Organizations typically base a variety of decisions concerning the employee partially on this rating. Performance management refers to the wide variety of activities, policies, procedures, and interventions designed to help employees to improve their performance. These programs begin with performance appraisals but also include feedback, goal setting, and training, as well as reward systems. Therefore, performance management systems begin with performance appraisal as a jumpingoff point, and then focus on improving individual performance in a way that is consistent with strategic goals and with the ultimate goal of improving firm performance (cf. Aguinis & Pierce, 2008). Performance management is a relatively recent term, however, and throughout the 100-year history reviewed here, the vast majority of Performance Appraisal Research Although interest in the evaluation of performance at work dates back to ancient China, and although there were efforts at establishing merit ratings in various settings as far back as the 19th century (Murphy & Cleveland, 1995), psychological research on performance rating did not begin in a serious way until the 1920s. This body of research can be traced back to Thorndike’s classic article, “A Constant Error in Psychological Ratings” (Thorndike, 1920). He identified what eventually became known as “halo error.” The assumption at the time was that errors of this sort would reduce the accuracy of ratings and therefore make them less useful. This article, along with articles by Rugg (1921) and Remmers (1931), which argued that graphic rating scales were especially prone to this error, helped drive appraisal research for at least the next 50 years. This article was published Online First January 26, 2017. Angelo S. DeNisi, A. B. Freeman School of Business, Tulane University; Kevin R. Murphy, Department of Personnel and Employment Relations, University of Limerick. Correspondence concerning this article should be addressed to Angelo S. DeNisi, A.B Freeman School of Business, Tulane University, 7 McAlister Drive, New Orleans, LA 70118. E-mail: 421 422 DENISI AND MURPHY This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. To help characterize the development of performance appraisal research, particularly research published in JAP, we sorted performance appraisal articles into eight substantive categories: (a) scale format research, (b) research evaluating ratings—articles examining various criteria for evaluating performance ratings (e.g., rater errors), (c) training research, (d) research on reactions to appraisals, (e) research on purpose of rating, (f) research on rating source, (g) research on cognitive processes—studies of information processing and judgment in rating, and (h) research on demographic effects. Historical Review of Performance Appraisal Research in JAP Performance appraisal has been the major focus of a large number of articles published in JAP. There were 94 articles dealing primarily with job performance measurement or performance appraisal published in JAP prior to 1970, several of which represent important contributions to the literature (e.g., Bingham, 1939; Hollander, 1957; Smith & Kendall, 1963), although most of them deal with rating scale formats and ways to reduce rating “errors.” There were also 30 articles dealing with performance appraisal since 2000, but it seems clear that the period 1970 to 2000 represented the heyday of performance appraisal research in JAP. During this period, JAP published 187 articles in which performance appraisal was the primary topic (we should also note that, during this period, there were also a number, but simply reported on a new rating scale that was developed for some job or reported data on some other type of performance measure [e.g., Ferguson, 1947; Rothe & Nye, 1958], and this is the main focus of our review). We analyzed the content of these 187 articles to identify trends in the topics covered during the period 1970 –2000. We grouped articles into 5-year spans and examined the content of JAP articles published 1970 –1974 (23 articles), 1975–1979 (29 articles), 1980 –1984 (34 articles), 1985–1989 (43 articles), 1990 –1994 (30 articles), and 1995–2000 (24 articles). Figure 1 illustrates the proportion in each content category for the six time periods studied. We conducted a similar analysis for the earlier and later periods; those data can be found in the online supplemental materials associated with this article, as can a list of especially influential articles in each area we discuss (Archival Table 1). There are three particularly noteworthy trends in Figure 1. First, scale format research was very popular in JAP, particularly from 1970 –1979, representing well over 40% of the performance appraisal articles published in this period (and, as noted in the previous paragraph, this was the case for the earlier period as well). In hindsight, this emphasis might be seen as regrettable, since Landy and Farr’s (1980) review of performance appraisal research lamented the unproductive nature of these scale format studies, and called for a moratorium on studies of scale formats, and, in fact, our data suggest this was the case, but as we shall discuss later, this research did help move the field forward. Figure 1. Trends in performance appraisal research, 1970 –2000. See the online article for the color version of this figure. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. PERFORMANCE APPRAISAL AND PERFORMANCE MANAGEMENT Second, starting in the 1980s, studies of the criteria used for evaluating ratings (i.e., criteria for criteria, such as rater errors, interrater agreement, rating accuracy) started to appear with some regularity; JAP published 26 articles on these topics between 1980 and 1997. Articles published in JAP during this period featured particularly lively discussions of the nature and consequences of halo error, and of the relationship between halo and other supposed errors in rating. Ultimately, this focus was also shown as somewhat misguided, but it was these articles that helped us understand why reducing rating errors was not the optimum criterion measure for evaluating appraisal systems Third, there was a dramatic spike in studies on cognitive processes in evaluating performance in the 1980s, primarily because of two influential review articles (Feldman, 1981; Landy & Farr, 1980) calling researchers’ attention to the importance of these processes. DeNisi (2006) and Ilgen, Barnes-Farrell, and McKellin (1993) provide excellent reviews of cognitive research on performance appraisal, much of which was published in JAP. Starting in 1990, there was a substantial drop in the popularity of studies of cognitive processes in performance appraisal, reflecting, in part, growing concern about the relevance of this work to the practice of performance appraisal in organizations (Ilgen et al., 1993). Nevertheless, this body of research made clear contributions to our understanding of how performance is judged (DeNisi, 2006; Ilgen et al., 1993) and provided useful suggesting for improving performance appraisal in organizations (e.g., behavior diaries). Fourth, training research showed a brief spike in the late 1970s, but never really emerged as a dominant area of research, and although there were other areas that showed intermittent peaks and valleys, there were no clear trends until recent interest in contextual performance. The Development of Key Concepts in Performance Appraisal Figure 1 illustrates some broad trends in performance appraisal research, but it does not fully capture how ideas developed in various parts of this field. A more detailed discussion of the issues dealt with by particular articles provides a more vivid picture of the concepts that came to dominate performance appraisal research. Rating Scales As noted above, Thorndike’s (1920) and Rugg’s (1921) article help set the stage for over 50 years of performance appraisal research. In the 1920s and 1930s, research was primarily concerned with ways to improve graphic rating scales or ranking methods (e.g., Ream, 1921). It is worth noting, however, that although a number of articles dealing with these two types of ratings appeared in JAP, the original work introducing the scales appeared elsewhere. Graphic rating scales were introduced by Paterson (1922), who described the scales developed by the Scott Company. Ranking methods were first used operationally by the U.S. Army in World War I, but the original work dates back at least a far as 1906 (Cattell, 1906), and the use of paired comparisons for establishing ranks dates back almost as far (e.g., Barrett, 1914). Knauft (1948) introduced the idea of using weighted checklists to rate performance. This research proposed a marked improve- 423 ment over simple lists of behaviors, and other studies seeking further improvements followed (e.g., Meyer, 1951). But the most important development in the area of checklists came with the introduction of the critical incidents technique, introduced by Flanagan in an article appearing in Personnel Psychology, and later fully explicated in Psychological Bulletin (Flanagan, 1954). Throughout the 1950s and 1960s, there were several articles appearing in JAP endorsing this type of scale and/or suggesting improvements (e.g., Kay, 1959). Furthermore, the critical incidents technique also led to the development of behavioral observation scales, which were first introduced by Latham and Wexley (1977) in an article in Personnel Psychology. Subsequently, several articles appeared in JAP pointing out problems with the use of these scales (e.g., Murphy & Constans, 1987; Murphy, Martin, & Garcia, 1982), and they never gained widespread popularity. The history and review of forced choice rating scales appeared in Psychological Bulletin (Travers, 1951), but the rating method gained popularity with a article by Sisson (1948) and a later article by Berkshire and Highland (1953). Later articles appearing in JAP proposed improvements in this technique (e.g., Lepkowski, 1963; Obradovic, 1970). Smith and Kendall’s (1963) classic article adopted methods introduced by Champney (1941) to develop scales for evaluating job performance, but were also based broadly upon critical incidents; these scales are commonly referred to as behaviorally anchored rating scales. There were a variety of rationales for these scales, but it was generally thought that the use of behavioral anchors provided a clear definition and a consistent frame of reference for both the dimensions to be rated and the various levels of performance. Over the years, variations on this scaling format were introduced, including mixed standard scales. This rating format, introduced by Blanz and Ghiselli (1972) in Personnel Psychology, asked raters to determine whether the performance of a ratee was better than, worse than, or about the same as the performance level exemplified by a behavioral example, and Saal (1979) introduced scoring systems for potentially inconsistent responses to this type of scale. Figure 2 presents examples of these different rating scale formats. By the time Landy and Farr’s (1980) review of performance appraisal research was published in Psychological Bulletin, it was becoming clear that variations in scale formats had only modest effects on the quality of rating data. That review arguably signaled an end to what was the most dominant line of research on performance appraisal—the search for scale formats that would solve the problems of subjectivity, inaccuracy, and lack of credibility that have, for so long, contributed to concerns over performance appraisal in the field. It should be noted, however, that research on rating scale formats has continued, albeit sporadically (e.g., Scullen, Bergey, & Aiman-Smith, 2005; dealing with forced distribution ratings). Attempts to improve rating scales represented a significant portion of the total body of research on performance appraisal and performance management published in JAP during its first 100 years, and from one perspective, these articles might be dismissed as unproductive. We do not agree. Although the search for a truly superior rating scale was not successful, this line of research pushed the field to more carefully anchor performance judgments in behavioral terms, which also improved the clarity and acceptability of performance ratings. Furthermore, given the attention to DENISI AND MURPHY 424 scale development in so many other areas of psychology during this time, this was a vein that had to be mined. Psychologists may never have moved beyond the view that substandard scales were holding back performance appraisal without this sustained effort to develop better scales. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Evaluating the Quality of Rating Data Much of the performance appraisal research appearing in JAP has been concerned with evaluating the quality of rating data—that is, assessing the reliability, validity, or accuracy of performance ratings. For example, Rugg (1921) used measures of reliability as the criteria for evaluating rating systems. In articles such as this, authors either implied or stated that they were interested in producing more “accurate” ratings, but accuracy was never directly measured. Instead, a system was “good” if it resulted in reliable ratings (e.g., Remmers, 1931), and even “better” if it produced equally reliable ratings with less time and effort (e.g., McCormick & Roberts, 1952). During the period 1920 –1970, the “holy trinity” of rater error measures was developed—that is, measures of halo, leniency/ severity, and central tendency/range restriction, starting with the first performance appraisal article published in JAP (Thorndike, 1920), which was concerned with halo error. Guilford and Jorgensen’s (1938) paper, “Some Constant Errors in Rating,” discussed concepts highly similar to leniency and central tendency error, although they did not use these precise terms, and error measures were the most common method of evaluating the quality of rating data, through the 1980s. Alternatives, such as evaluating the convergent and discriminant validity of ratings (Kavanagh, MacKinney, & Wolins, 1971) and applications of factor analysis 1. Graphic Rating Scale (probably can be viewed as the default option): How would you evaluate this employee’s attitude? __________________________________________________ 1 2 3 4 5 Very Poor Average Good Outstanding Poor 2. Ranking Methods No scale, rater simply instructed to rank order all subordinates from the best to the worst based on overall performance or effectiveness. 3. Forced Choice Rating Scale (Here two items have been determined to discriminate between overall good and poor performers, BUT all four are about equally favorable as a description. Only when the rater chooses the items that discriminate, does the ratee received any credit. None of the data from the indices are revealed to the rater. Choose the TWO statements that best fits this employee. This employee … Discriminability Favorableness Index Index a. Usually finishes work assignments on schedule +2.0 +3.0 b. Usually reports for work on time +1.8 +2.7 c. Is usually in a good mood + .4 +2.8 d. Rarely wastes time on the job + .5 +2.7 4. Forced Distribution Rating Scale Sort all employees into the following three categories, noting the percentage that should be assigned each category: 25% 50% 25% _________________I___________________I___________________ BELOW AVERAGE AVERAGE ABOVE AVERAGE Figure 2. Examples of rating scale formats proposed to improve ratings. See the online article for the color version of this figure. for evaluating halo (Landy, Vance, Barnes-Farrell, & Steele, 1980), were suggested, but these methods did not displace traditional rater error measures. There were, however, a few articles that attempted to assess rating accuracy more directly. For example, Mullins and Force (1962) compared ratings of employee characteristics such as carelessness with scores on tests designed to measure carelessness, on the assumption that raters whose evaluations matched test scores were more accurate. Wiley and Jenkins (1964) compared the ratings of individual raters with the mean across many raters, and argued that individuals who were closest to the mean were more accurate. Borman (1977, 1979) developed a method of evaluating rating accuracy that involved comparisons between the ratings obtained from a single rater with the average of ratings obtained from multiple experts operating in optimal rating conditions. In practice, this method required strict control over the stimuli being rated, and typically involved having both subjects and experts rate videotaped performance segments, and numerous JAP articles during the 1980s applied these methods. The development of practical methods of evaluating rating accuracy stimulated debates about precisely how accuracy should be defined. Most studies of rating accuracy relied on one or more of the accuracy indices articulated by Cronbach (1955), such as elevation (accuracy in the overall level of rating) and stereotype accuracy (accuracy in distinguishing dimensions on which ratees tend to perform well from those on which rates tend to perform poorly). Sulsky and Balzer’s (1988) review suggested that different accuracy measures were not interchangeable, and also noted that the use of rating accuracy criteria limited appraisal research to laboratory studies and to evaluations of short performance segments. In fact, both rater error and rating accuracy measures can be problematic, and this point had been made by several authors over the years. For example, Guilford and Jorgensen (1938) noted, error measures required knowledge of the true distributions and intercorrelations among performance dimensions. Therefore, assuming that halo error was present, for example, if the intercorrelations among ratings were too high, made no sense without data concerning the levels of true relationships among dimensions. Bingham’s (1939) discussion concerning “true halo” made many of the same points. Furthermore, it was widely assumed that ratings that exhibited more reliability or fewer rater errors must also be more accurate. This assumption persisted for quite a long period of time, despite a number of articles arguing that this was not true (e.g., Buckner, 1959; Cooper, 1981). Murphy and Balzer’s (1986) article, demonstrating that traditional rater error measures were uncorrelated with any of the four accuracy measures described by Cronbach (1955), essentially ended the field’s reliance upon rater errors, although some recent research on the distribution of ratings suggests that there may be some benefit to less “lenient” ratings (e.g., O’Boyle & Aguinis, 2012). Research in this area, then, contributed to the field primarily by pointing out the problems with more traditional criteria for evaluating the effectiveness of appraisal systems. Although subsequent research suggested that rating accuracy might not be the best criterion measure (e.g., Ilgen, 1993), this line of research led us away from traditional error measures to accuracy measures and eventually to measures that reflected ratee perceptions of fairness and accuracy. PERFORMANCE APPRAISAL AND PERFORMANCE MANAGEMENT This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Training Levine and Butler (1952) provided the first description of a rater training program in JAP. They use a variety of training methods, but one stands out as being prophetic—that is, they lectured raters on the nature of rater errors and cautioned them to avoid them. Similar approaches were applied by a number of other scholars over the years (e.g., Bernardin & Walter, 1977; Borman, 1975). This training “worked” in the sense that it led to lower levels of intercorrelation and lower mean ratings, which was taken to mean less halo and leniency error. But drawing upon the research described above, training researchers began to realize that training raters to avoid rating errors did not necessarily lead to more accurate ratings and could produce decreased accuracy (Bernardin & Pence, 1980; Hedge & Kavanagh, 1988). This led researchers to modify training, for example, by adding detailed discussion of the behavior anchors on rating scales to discussions of rater errors (Ivancevich, 1979) or adding training on how to record behaviors accurately (Thornton & Zorich, 1980), which seemed to help. Borman (1979) described a training approach that foreshadowed what would become the dominant method of rater training—that is, Frame of Reference (FOR) training. He showed raters videotapes of performance, asked them to rate the tapes, then discussed the most appropriate ratings for each candidate (“true score”) and why this was appropriate. Bernardin and Buckley (1981) formally introduced the concept of FOR training, which Woehr (1994) described as including definitions of performance dimensions, samples of behavioral incidents representing each dimension, and an indication of the level of performance represented by each incident, followed by practice and feedback using these standards. Several studies provide evidence for the effectiveness of FOR training for instilling a uniform theory of work performance in all raters (e.g., Athey & McIntyre, 1987; Gorman & Rentsch, 2009; Pulakos, 1984). However, as Uggerslev and Sulsky (2008) note, FOR training is most successful for raters whose theory of work performance prior to training is already similar to the theory FOR attempts to instill. Two broad themes have dominated research on rater training: (a) how to train raters, and (b) how to determine whether or not training works. On the whole, progress has been more substantial in determining the content of rater training than in determining its effectiveness. There is consensus that training raters what not to do (e.g., training them to avoid rater errors) is ineffective. There is also consensus that training raters to adopt consistent conceptions of what represents good versus poor performance and what behaviors and competencies constitute performance is beneficial. Reactions to Appraisals There was little research on reactions to appraisals until the 1970s. The research that began at that time focused on ratee satisfaction and perceptions of fairness, for the most part (e.g., Wexley, Singh, & Yukl, 1973) Research on perceptions of fairness date back to two studies by Landy and his associates (Landy, Barnes, & Murphy, 1978; Landy, Barnes-Farrell, & Cleveland, 1980), which found that identifying goals to improve weaknesses, frequent evaluations, and rater knowledge were important predictors of perceptions of fairness and rating accuracy, while the later study also found that consistency among feedback sources was 425 also important. A later meta-analysis (Cawley, Keeping, & Levy, 1998) reported that participation (in various forms) was highly correlated with employee reactions, and pointed to the importance of justice perceptions in this process. Several articles, appearing elsewhere, also focused on the role of justice perceptions in reactions to performance appraisal (e.g., Folger, Konovsky, & Cropanzano, 1992), which was confirmed in other empirical articles (e.g., M. S. Taylor, Tracy, Renard, Harrison, & Carroll, 1995). This line of research has been especially important because, when combined with the research on rating errors described above, it helped move the field to consider other types of outcome measures that could be used to evaluate appraisals systems. In fact, justice perceptions have become an important part of later models of performance management (e.g., DeNisi & Smith, 2014), and this is suggested as an important area for research in the future. Purpose for Appraisal Meyer, Kay, and French (1965) noted that performance appraisals are often used for multiple reasons, and that these reasons can lead to conflicting goals for appraisal, a finding empirically confirmed by Cleveland, Murphy, and Williams (1989). Studies showed that the purpose for which ratings were to be used affected what kinds of information were sought as well as how that information was used to make decisions (e.g., Williams, DeNisi, Blencoe, & Cafferty, 1985; Zedeck & Cascio, 1982). Also, although organizations have their purpose for collecting ratings, raters also have purposes and goals in mind when making ratings, and Murphy, Cleveland, Skattebo, and Kinney (2004) found that the goal of the rater at the time of the evaluation affected several properties of the ratings given. This research did not have a large impact on the practice of performance appraisal. The various purposes to which organizations apply appraisal information from Cleveland et al. (1989) continue, and it is extremely rare to find a case in which different appraisals are conducted for different purposes. Rating Sources Performance ratings are usually obtained from supervisors, but it has long been recognized that other sources might be tapped to obtain performance evaluations (e.g., subordinates, self-ratings). As early as the 1940s, Ferguson (1947) used peers, supervisors, and subordinates in developing appraisal scales, but he did not obtain performance ratings from all three sources. Authors of several other articles (e.g., Bendig, 1953; Fiske & Cox, 1960) discuss the use of self-ratings and/or peer ratings, but do not directly compare the information obtained from self- or peer ratings with supervisory ratings. Springer (1953) is the first JAP article to specifically ask the question of whether “supervisory personnel and co-workers agree in their ratings” (p. 347). His findings (modest positive correlations between ratings of the same dimensions by peers and supervisors) set the pattern for virtually every subsequent study comparing ratings from different sources, but this did not discourage further research on agreement (see review by Heidemeier & Moser, 2009). This research had its greatest impact in the role played in recommendations for multisource or 360-degree appraisals (i.e., This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 426 DENISI AND MURPHY rating systems in which feedback is collected from multiple sources and feedback pooled by source is provided to rates). Much of this work was based on research by Lawler (1967), published in JAP, including London and Smither’s (1995) article suggesting that feedback from multiple sources could influence subsequent goals as well as performance. Smither, London, and Reilly (2005) also presented a theoretical model as well as meta-analysis results supporting multisource appraisals, but Greguras and Robie (1998) reported that none of the rating sources showed high levels of reliability, while Seifert, Yukl, and McDonald (2003) suggested that the use of a coach could improve the effectiveness of these programs. Research on these programs progressed through a series of steps, first asking whether it was possible to obtain performance ratings from multiple sources, then asking whether ratings from these sources were comparable, and, finally, asking whether multisource feedback was effective. The results of his research suggest that obtaining information from different sources can be useful, but that different sources differ systematically in the conclusions they suggest about overall performance levels, and that evaluations from others are likely to be less favorable than selfevaluations. There remain questions about the effectiveness of these systems, however, and we must conclude that the jury is still out on the last issue (cf. DeNisi & Kluger, 2000). Demographic Effects The possibility that performance ratings might be affected by demographic variables such as race, gender, or age has long been recognized as a potential source of employment discrimination. In one of the first published studies of race differences in performance measures, Dejung and Kaplan (1962) examined ratings of combat aptitude as a function of the race of both raters and ratees. They found that Black raters favored Black ratees, but White raters did not favor White ratees, and this same pattern of results was reported in several studies and in a subsequent meta-analysis discussed later in this section. Bass and Turner (1973) examined Black–White differences in both performance ratings (pooled over multiple raters for most rates) and objective performance measures (number of errors, number of miscounts, attendance) for bank tellers. They reported significant differences, favoring White tellers, but noted that these were generally small, and were smaller for ratings than for objective measures. This pattern of results has been replicated in most subsequent studies. During the next several years, there were several notable indirect studies on demographic effects on performance evaluations. Hamner, Kim, Baird, and Bigoness (1974) had students observe the performance of confederates (White and Black, male and female) in a work sample task, and they reported small main effects for race and Rater X Ratee interactions. Schmitt and Lappin (1980), in a similar study using videotapes performance samples, replicated this pattern of Rater X Ratee race interactions, with Black raters giving especially high ratings to Black ratees. Several studies have taken an even more indirect approach, asking subjects in laboratory studies to read vignettes and make judgments about hypothetical ratees. Schwab and Heneman (1978) showed small, but sometimes significant, differences in ratings as a function of rater and ratee age. Rosen and Jerdee published several vignette studies (e.g., Rosen & Jerdee, 1976) suggesting that there were potential sex and age biases in evaluations. However, there are reasons to believe that the findings of these laboratory studies overestimate the effects of the demographic characteristics in the appraisal process. Wendelken and Inn (1981) argued that demographic differences are made especially salient in laboratory studies in which other ratee characteristics are tightly controlled, and in which raters are untrained and have no prior knowledge of, and no relationship with, ratees. Murphy, Herr, Lockhart, and Maguire’s (1986) meta-analysis confirmed that vignette studies do indeed tend to produce larger effects than do studies involving the observation of actual performance. The results of several large-scale studies provide better insight into the effects of the demographic characteristics of ratees on performance ratings. Pulakos, White, Oppler, and Borman (1989) reported some significant race effects, but also noted that effect sizes were generally quite small and did not always favor White ratees (see also Kraiger & Ford, 1985; Waldman & Avolio, 1991), whereas studies by Sackett, DuBois, and Noe (1991) and Sackett and DuBois (1991) suggested that the overall pattern of race effects might be more complex than had been suspected. This body of research shows that in some settings (especially laboratory studies), demographic variables can influence performance ratings. However, it also suggests that in the field, these variables do not have a large effect on performance ratings. Variables like age, gender, or race influence a number of things that happen in organizations, but the outcomes of performance appraisals do not seem to be strongly influenced by these demographic variables. Given the evidence or racism, sexism, and ageism in many other settings, the question of why performance ratings do not seem to show these same biases is an important one. It is possible that as information about performance is acquired over time, that information eventually swamps whatever stereotypes influence judgments made in less information-rich environments, but at present, this is simply a hypothesis awaiting convincing tests. Cognitive Processes Several reviews and theory articles (e.g., DeNisi, Cafferty, & Meglino, 1984: Feldman, 1981; Landy & Farr, 1980) sparked interest in the cognitive processes involved in performance rating, particularly in the way raters acquire, organize, recall, and integrate information about rate performance. Over the next 10 to 15 years, a number of studies, mostly laboratory experiments involving relatively short videotapes of performance, were published in JAP. These studies dealt primarily with the acquisition, organization, and encoding of performance information, and with the recall and integration of that information. Various studies examined the role of rating purpose (Kinicki, Hom, Trost, & Wade, 1995; Williams, Cafferty, & DeNisi, 1990), and rater affect (Robbins & DeNisi, 1994), as well as individual differences (e.g., Bernardin, Cardy, & Carlyle, 1982), on cognitive processes, and DeNisi, Robbins, and Cafferty (1989) reported that keeping behavioral diaries could aid recall an encoding. Researchers also found that the organization of information in memory could be affected by categories existing in raters’ minds prior to observing behavior (e.g., Kozlowski & Kirsch, 1987). Still others reported that rater schema for organizing information influenced This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. PERFORMANCE APPRAISAL AND PERFORMANCE MANAGEMENT what was attended to and later recalled (e.g., Nathan & Lord, 1983), and therefore could influence the accuracy if what was actually observed and recalled (e.g., Lord, 1985). Interestingly, these findings tied back to the work on frame of reference training, suggesting that this training could lead raters to adopt a consistent and appropriate set of categories for organizing information, which can, in turn, enhance accuracy in recall and evaluation (e.g., Athey & McIntyre, 1987; Woehr, 1994). But it should be noted that although DeNisi and Peters (1996) demonstrated similar effects for diary keeping and a structured recall task in one of the few field studies involving cognitive processes, Murphy, Garcia, Kerkar, Martin, and Balzer (1982) reported that accuracy in evaluating performance is mostly unrelated to accuracy in observing and encoding behavior. Furthermore, a number of studies suggested that memory for behaviors was strongly affected by general impressions and overall evaluations (e.g., Murphy & Balzer, 1986), and even the anchors used in behaviorally based rating scales (Murphy & Constans, 1987). More critically, Murphy, Martin, et al. (1982) reported that these effects could overwhelm the actual memory for specific behaviors exhibited by a ratee. Studies of cognitive processes in performance evaluation made a definitive contribution by considering the ways in which raters obtain, process, and retrieve information about performance. On the other hand, this line of research had a relatively short shelf life, emerging as a major force in the 1980s, but tailing off dramatically by the mid-1990s. This shift was driven, in part, by the recognition that performance appraisal is not a simple judgment task, but rather a task that occurs in a complex and demanding environment and that involves motivational as well as cognitive variables (Murphy & Cleveland, 1995; Murphy & DeNisi, 2008). Performance Management Research Given our 100-year perspective, the history of research on performance management is much more limited than that for performance appraisal. Even the term “performance management” is much more recent, and so there is much less history to describe. However, as we shall discuss, there has certainly been a history of research on some of the important components of performance management, such as feedback and goal setting. This research has been focused on improving the performance of individuals, however, and the ultimate goal of performance management systems is to improve firm-level performance. But although it has often been assumed that improving the individual performance would ultimately improve firm-level performance as well, establishing meaningful links between changes in individual performance and changes in firm performance has been an elusive goal (cf. DeNisi & Smith, 2014). We view the research on performance management as falling into three broad categories. First, there are the articles (or mostly books) that attempt to describe the entire performance management process and suggest how to improve it. Second are the articles that deal with specific aspects of the performance management process. In general, these articles are concerned with improving individual performance, and address one type of performance management intervention in isolation without discussing it in the wider perspective of the entire process. Finally, there are the articles that focus on improving firm-level performance and 427 how Human Resources (HR) practices can influence performance at that level. The Performance Management Process Performance appraisal has usually been considered an important aspect of performance management, but it would seem that the best hope of establishing a link between individual performance improvement and firm performance improvement would be to consider performance appraisal (either in its formal, annual guise or in terms of more frequent, less formal assessments) as only one of a broader set of activities that entail aligning staffing, performance feedback, incentives, and supervision with the strategic goals of organizations. Rather than just referring to ways in which organizations use performance appraisal information to improve performance, then, performance management would be defined as this broader set of HR activities, as has been suggested in books (e.g., Aguinis, 2013; Pulakos, Mueller-Hanson, O’Leary, & Meyrowitz, 2012) as well as publications in other journals (e.g., DeNisi & Smith, 2014; Kinicki, Jacobson, Peterson, & Prussia, 2013). But the vast majority of this work describes models and techniques rather than actually testing the effectiveness of these programs. Improving Individual Performance There has been a considerable body of research examining ways to improve individual performance and productivity, and much of it has appeared in JAP. A good example of this is the research on ProMES, a system that combines feedback, goal setting, and incentives in attempt to improve productivity (e.g., Pritchard, Harrell, DiazGranados, & Guzman, 2008; Pritchard, Jones, Roth, Stuebing, & Ekeberg, 1988). Interestingly, as research began to focus on performance management, the underlying theoretical models switched from measurement-oriented models to motivational models (e.g., DeNisi & Pritchard, 2006). That is, rather than focusing on the accuracy of the ratings, the research began looking at what drove employees to try to improve their performance. The topic of feedback meant to improve performance has also been featured in several articles from JAP, including an influential review of the literature on feedback from the late 1970s (Ilgen, Fisher, & Taylor, 1979) as well as some earlier work on feedback (e.g., Butler & Jaffee, 1974). Feedback research has continued to appear in the journal (e.g., Northcraft, Schmidt, & Ashford, 2011), including articles dealing with conceptual issues raised elsewhere in a major review by Kluger and DeNisi (1996; e.g., Vancouver & Tischner, 2004). Likewise, articles dealing with the role of incentives and goals on performance have been published in JAP over the years (e.g., Camman & Lawler, 1973; Ronan, Latham, & Kinne, 1973). Improving Firm Performance There is also a considerable body of research indicating how HR practices can influence firm performance when they are implemented as part of a larger scale effort (e.g., Huselid, 1995; Jackson, Schuler, & Jiang, 2014; Ployhart & Moliterno, 2011). Many of these have appeared in other journals, but several have been published in JAP (e.g., Aryee, Walumbwa, Seidu, & Otaye, 2012; Crook, Todd, Combs, Woehr, & Ketchen, 2011). What is far from 428 DENISI AND MURPHY clear is what combinations of HR practices make a difference (and whether performance evaluation and feedback is part of whatever combinations work) and why some practices work and others do not. DeNisi and Smith’s (2014) model of the performance management process suggests several useful avenues for research on these questions. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Contributions of Performance Appraisal and Performance Management Research The history of research on performance appraisal and management is not isomorphic with the history of articles on these topics in the JAP. As we shall discuss, articles published in JAP have more influence in some areas of research than in others. Based on our review of this literature, however, two overall conclusions seem justified. First, the overall contribution of 100 years of research on performance appraisal has been much greater than it has relative to performance management. Second, there are specific areas in which the contribution of articles published in JAP has been substantial, but sometimes in quite indirect ways. For example, we can consider the contribution of studies of rating scale formats. Although we believe that this research failed to demonstrate that the right rating format would make a big difference in the quality of performance ratings, it was necessary to actually conduct this research in a rigorous way in order to reach that conclusion. Furthermore, this work eventually led to an appreciation for the importance of ratee perceptions of fairness and accuracy, and JAP is where much of that research was published. This latter contribution was especially important for research on ratee reactions to appraisals (e.g., Taylor et al., 1995), as well as to subsequent models of performance management (e.g., DeNisi & Smith, 2014). Studies of criteria for evaluating ratings provided a similar pattern of contribution. Two early articles (Bingham, 1939; Thorndike, 1920) stimulated a considerable body of research on halo error (most of which was published between 1970 and 2000), but much of this work proved less useful for evaluating ratings (given the continuing difficulty in sorting true from illusory halo, leniency, and the like) than for helping us understand the way judgments about performance are made. Also, as with research on rating scale formats, this research had to be carried out in a rigorous way, in order for us to better understand judgment processes in this area, and, again, the vast majority of that research was published in JAP. Studies of the relationships between the demographic characteristics of raters and rates proved to be very important for understanding the effects of ratings on employees (e.g., Kraiger & Ford, 1985; Schmitt & Lappin, 1980), and, in our view, this stream of research represents one of the real success stories for research published in this journal. Both JAP studies and meta-analyses that include many JAP articles (e.g., Bowen, Swim, & Jacobs, 2000) suggest that although there are some differences in the performance ratings received by women versus men or by members of different racial and ethnic groups, these differences are usually quite small. These findings loom large in discussions of the construct validity and the fairness of performance ratings. Research on rater training showed the familiar pattern of fits and starts, which characterize the development of important concepts in many fields of psychology. In particular, much of the early work in this area dealt with what were probably misguided efforts to encourage raters to avoid rater errors. However, subsequent research on rater training documented several effective methods for increasing the accuracy of ratings, particularly frame of reference training. Again, JAP has made notable contributions to our understanding of how and why this method of training works. Finally, we believe that studies of the cognitive processes involved in evaluating others’ performance made a modest but worthwhile contribution. This may reflect our bias (as active contributors to this line of research), but we believe this line of research advanced the science of evaluating judgment, while spurring very useful discussions of what can and what cannot be learned from laboratory studies that mimic some aspects of performance appraisal and omitted others (e.g., Murphy & Cleveland, 1995). Despite the fact articles published in JAP have made many meaningful contributions to the literature, we believe it is fair to say JAP has not always been highly influential in the development of the main concepts, theories, and approaches that characterize current thinking in performance appraisal. For example, Murphy and Cleveland (1991, 1995) published two widely cited books reviewing performance appraisal and suggesting new directions for performance appraisal research. The broad theme of both books is the need to understand the context in which performance appraisal is carried out, how the motives of the participants (both raters and rates) shape appraisal processes and outcomes, and the implications of these two factors for evaluating the validity and usefulness of performance ratings. Although both books cited a number of articles published in JAP, it is fair to say that the research that had the strongest influence on the conceptual development of the models and approaches in these books appeared in outlets other than JAP. In fact, we can summarize the contributions of research published in JAP to the field of performance appraisal by stating that, with few exceptions, the journal was not the home of the theories or conceptual models that guided the field, but was, instead, where these models were tested and where critical technical issues were addressed. Understanding the contribution of the JAP to the performance management process requires some context—there have been very few empirical articles appearing in any journal in our field which have actually tested performance management programs. The work of Pritchard and his associates with PRoMES (cf., Pritchard, Harreell, Diaz-Grandos, & Guzman, 2008), which seeks to improve productivity by applying ideas from several motivational theories, comes close, however, and much of the empirical work concerning ProMES was published in JAP (e.g., Pritchard, Jones, Roth, Stuebing, & Ekberg, 1988). But we could identify no empirical articles in our field (published in JAP or elsewhere) that have demonstrated how improving individual level performance can be leveraged to improve firmlevel performance. Thus, we are left with conceptual/theoretical work explaining how such systems could be developed, but this work has been confined primarily to books and book chapters by either academicians (e.g., Aguinis, 2013; DeNisi & Smith, 2014) or practitioners (e.g., Pulakos et al., 2012). As noted, though, there have been a number of articles appearing in JAP that have added to our understanding of how bundles of HR practices can help improve firm-level performance. PERFORMANCE APPRAISAL AND PERFORMANCE MANAGEMENT Finally, there have certainly been a large number of articles that have focused upon how various performance management techniques such as feedback, goal setting, or incentive pay can influence individual-level performance, and much of this work has appeared in JAP. Thus, it is fair to conclude that JAP has made contributions to many of the components of performance management, but there is no credible empirical work, in JAP or elsewhere, that allows us to determine how performance management might actually work. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. What Have We Learned and What Do We Need to Do? Our title included a question mark suggesting potential doubts about whether the substantial body of research published in the last 100 years in JAP has made a substantial contribution to our understanding of performance appraisal and performance management. The answer is both “yes” and “no.” It should be clear that we have come a long way from examining rating scale formats to determine their effects on rating errors, and JAP has contributed substantially to this progress. We have certainly learned that the specific format of the rating scale used is not the most important consideration in developing appraisal systems and that traditional error measures are not the best way to evaluate such systems. We have learned that demographic characteristics may have less influence on ratings than we had believed, that some rater cognitive processes are related to appraisal decisions, and that it is possible to train rates to do a better job. Certainly, these accomplishments can be considered progress. However, perhaps the most significant progress we have made during this time is to come to better appreciate the critical influence of the context in which performance appraisal occurs on the process and outcomes of appraisal (Murphy & DeNisi, 2008), and the role of JAP in this area is smaller and more indirect. Performance appraisal is used for a variety of purposes in organizations (Cleveland et al., 1988), and these purposes influence the way performance is defined (e.g., task performance vs. contextual performance; Podsakoff, Ahearne, & MacKenzie, 1997) and the way raters and ratees approach the task of performance appraisal (Murphy & Cleveland, 1995). The appraisal effectiveness model proposed by Levy and Williams (2004) summarizes much of the research on the role of social context and emphasizes the importance of rate reactions to appraisals and the acceptability of ratings, and some of the work summarized in this review has appeared in JAP. However, most of the research published in JAP has been decontextualized, examining different facets of the rating process (e.g., cognitive processes, rating scales, rater training) in isolation, and it has become clear that we will not make progress in understanding how or why appraisals succeed without considering why appraisals are done in the first place, and how the climate, culture, norms, and beliefs in organizations shape the appraisal process and the outcomes of appraisals. Contextualizing performance appraisal research implies paying attention to when and why performance appraisal is carried out and the contextual variables that are likely to be important range from quite distal (e.g., national cultures) to quite proximal (e.g., supervisor-subordinate relationships). For example, there may be aspects of national culture (or organizational culture) that make it less acceptable to give anyone negative feedback, and this may put 429 pressure on raters to intentionally inflate ratings. In fact, we know little about how culture and societal norms really affect appraisal decisions and processes; JAP has made few contributions here. There is descriptive research that indicates that different practices and policies are more likely in some parts of the world than in others (e.g., Varma, Budhwar, & DeNisi, 2008), but we do not fully understand how cultural norms may make certain practices more or less effective. Also, we need more research on the effectiveness of individual-level performance management techniques in different cultures. The archive for this issue also includes a model of various factors that might affect performance appraisal processes and changes in individual performance. This model is adapted from Murphy and DeNisi (2008). At the most fundamental level, the question mark in our title really refers to the uncertainty in moving from the level of individual-level performance to firm-level performance. DeNisi and Smith (2014) concluded that although we have learned a great deal about how to improve individual performance through appraisal and performance management programs, there is no evidence to show that improving individual-level performance will eventually lead to improvements in firm-level performance. As noted earlier, it has always been implied or assumed that improving individual-level performance would eventually lead to improvements in firm-level performance. The ongoing failure to establish a clear link between individual and performance that leads us to raise questions about overall progress in this field. Even if we succeed in using performance appraisal, feedback, and other components of performance management to improve individual job performance, it is not clear that this will lead to more effective organizations. We believe that identifying how (if at all) the quality and the nature of performance appraisal programs contribute to the health and success of organizations is a critical priority. JAP is not alone in its failure to address this priority; the research literature in the organizational sciences simply has not grappled with this question in a credible way. In conclusion, we believe that JAP has made some worthwhile contributions to our understanding of performance appraisal and performance management. More important, JAP can and should have a critical role in the future progress of our field. JAP has always placed a strong emphasis on rigorous empirical test of theories and models, and this is an orientation that is not universally shared across journals in this domain. As a consequence, we believe that JAP should be a natural home for rigorous tests of performance management programs and their components. It is disconcerting to see how much discussion of performance management exists, and how little evidence there is about how it actually works. It is our hope that JAP can take a lead in combining the concern for the organizational performance, often shown in other parts of the organizational sciences, with its traditional concern for scientific rigor to produce a better understanding of how and why performance appraisal and performance management actually function in organizations, and how attempts to evaluate and improve individual performance influence the lives of employers and employees and the organizations in which they are found. Specifically, we believe that JAP should seek to publish research that (a) is conducted in organizations settings, (b) involves processes and outcomes with real stakes for participants (for example, studies of performance appraisals that are used for pro- DENISI AND MURPHY This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 430 motion and pay decisions), (c) includes assessments of both distal and proximal context variables, and (d) includes assessments of performance/success at a range of levels, including individual, group, and firm performance measures when possible. 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Switzer, III This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Clemson University Despite widespread use of forced distribution rating systems (FDRSs), the potential for this performance appraisal method to lead to adverse impact (AI) in a layoff context has yet to be examined empirically. Thus, the current study uses a Monte Carlo simulation to examine the likelihood of encountering AI violations when an FDRS is used in the context of layoffs. The primary research questions included an examination of how AI violations change depending on the definition of the employment action (i.e., retention vs. layoff), the length of the repeated layoffs, and whether or not laid off employees are replaced each year. The current study also examined the impact of the size of the organization, the percentage of the workforce laid off, and the type of AI calculation method used on the likelihood of AI violations. Results suggest that defining the employment action as layoffs (rather than as retentions) may result in a greater likelihood of AI violations, and AI violations are likely to peak in the 1st year of use. Further, replacing laid off employees may result in higher levels of AI over time as compared with not replacing layoffs. Additionally, the greatest risk for AI occurs when the organization size is large (i.e., N ⫽ 10,000) and when certain AI calculation methods are used. Results are discussed in terms of their practical and legal implications for organizations. Keywords: performance appraisal, forced distribution rating system, relative performance rating system, FDRS, adverse impact Supplemental materials: bottom 10%, and do it every year” (General Electric, 2000, p. 6). Simulation research has indicated that the practice of using an FDRS does indeed have the potential to increase the quality of performance across time in an organization when paired with reliable, valid selection instruments (Scullen, Bergey, & AimanSmith, 2005). Whereas as many as 20% of Fortune 500 organizations have bought into the idea of using an FDRS (Grote, 2005; Meisler, 2003), the practice is seen as controversial by many others (Bates, 2003; Dominick, 2009; Stewart, Gruys, & Storm, 2010). Such a system that continually removes the lowest performing employees is frequently seen as unfair in the eyes of both performance raters and bottom performers (Schleicher, Bull, & Green, 2009). In addition, reviews of the legal landscape have identified layoffs resulting from performance appraisal (PA) as an area with increased legal activity (Foster, 2006; Lee, Havighurst, & Rassel, 2004; Martin, Bartol, & Kehoe, 2000). Indeed, several large organizations that have implemented an FDRS, including Conoco, Ford Motor Company, Goodyear Tire, Capital One, and General Motors, have had class action lawsuits filed against them and have paid large cash settlements to former employees who claimed that the rating system resulted in discrimination against various protected groups (including African Americans, women, and older workers; Scullen et al., 2005). Whereas research has demonstrated that an FDRS can improve workforce potential, less is known about the other side effects of implementing such a system, par- Many top corporations claim the only way to perform at the highest potential is to implement a forced distribution rating system (FDRS) that rewards the top employees and removes the bottom employees each year. These so-called rank and yank systems have been implemented across many large organizations, and many laud them for their organization’s success (Bates, 2003; Kwoh, 2012). Included among this group is one of their most well-known proponents, former General Electric CEO Jack Welch, who has said that “leaders must not only understand the necessity to encourage, inspire and reward that top 20% . . . they must develop the determination to change out, always humanely, that This article was published Online First June 16, 2014. Gary W. Giumetti, Department of Psychology, Quinnipiac University; Amber N. Schroeder, Department of Psychology, Western Kentucky University; Fred S. Switzer, III, Department of Psychology, Clemson University. An earlier version of this study was presented in 2011 at the 26th annual meeting of the Society for Industrial–Organizational Psychology, Chicago, Illinois. We gratefully acknowledge assistance from Lindsay E. Sears during initial conceptualization of the study design. Correspondence concerning this article should be addressed to Gary W. Giumetti, Department of Psychology, Quinnipiac University, 275 Mount Carmel Avenue, CLAC-1, Hamden, CT 06158. E-mail: gary.giumetti@ 180 FORCED DISTRIBUTION RATINGS AND ADVERSE IMPACT ticularly the potential for adverse impact (AI) when used for layoffs. Thus, in the current article, we aimed to bridge this gap in research by examining the impact of an FDRS on AI over time using a Monte Carlo simulation. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. FDRSs An FDRS is a PA technique that minimizes rating leniency by requiring raters to evaluate employees by sorting them into predetermined performance categories (Guralnik, Rozmarin, & So, 2004; Murphy & Cleveland, 1995). The FDRS is an improvement over simple ranking procedures, which require that each employee in a particular position or entire department be given a specific rank, as simple ranking procedures might become quite cumbersome in large departments or organizations. With an FDRS, only the top and bottom performers need to be identified, so the rater’s task becomes more manageable (Murphy & Cleveland, 1995). In addition, as the FDRS approach is a relative rating technique in which ratings are derived by comparing each employee’s performance with that of his or her coworkers, FDRS ratings can be used in a variety of ways, including performance development, promotion, compensation, job assignments, and layoffs (Schleicher et al., 2009). With regard to prevalence, some have estimated that between 8% and 20% of organizations use an FDRS approach (Grote, 2005; Society for Human Resource Management [SHRM], 2005). In a 2005 survey, the SHRM gathered responses of 330 human resources managers who indicated that more than 8% of organizations might use an FDRS to terminate employees (SHRM, 2005). The use of an FDRS is similar to the practice of traditional score banding in selection, in which candidates are placed into groups (e.g., A, B, C, D) based on their scores on a predictor, and then the organization selects individuals only from the top band, if possible (Aguinis, 2004). That is, both FDRSs and traditional score banding involve grouping individuals on the basis of their scores on some measure and then treating all grouped individuals the same with regard to a personnel decision (e.g., hiring or firing). Both score banding and FDRS approaches have been seen as controversial practices by organizations (e.g., Bates, 2003; Campion et al., 2001; Sparrow, 2009), and mixed messages have appeared in the popular press and the scientific literature on both practices. In favor of the FDRS approach, several studies have advocated that this approach compels managers to give honest feedback, which helps organizations to avoid rater biases (such as leniency or favoritism) and encourages instead that raters make clear distinctions between the highest and lowest performing employees (Berger, Harbring, & Sliwka, 2013; Lipman, 2012; Olson & Davis, 2003). In addition, the FDRS approach helps to establish a norm for intolerance of subpar performers (Guralnik et al., 2004). Additionally, others have noted that using an FDRS helps organizations to focus on the performance criteria that are important to them and encourages employees to work hard to obtain the highest ranking (Berger et al., 2013; Dominick, 2009). Further, two simulation studies have demonstrated that an FDRS could positively impact the performance quality of an organization over time (Mulligan & Bull Schaefer, 2011; Scullen et al., 2005). Lastly, the practice still has several vocal advocates, including LendingTree, American International Group, and MassMutual (Kwoh, 2012; Lipman, 2012). 181 Critics of the FDRS method, however, argue that it discourages employee professional development efforts, increases the likelihood of discrimination lawsuits, and negatively impacts teambased work environments (Dominick, 2009). Additionally, recent research by Cook (2012) revealed that using an FDRS may have a negative impact on employee motivation and may also breed competition. Others have also noted the potential negative impact on employee morale (Lipman, 2012), and some authors have even suggested that an FDRS may create opportunities for employee sabotage (Berger et al., 2013). In addition to its impact on employees being rated, managers who are performing the ratings may also have negative perceptions of this process. In a study by Schleicher et al. (2009), raters perceived FDRS methods to be more difficult when their ratings had administrative consequences than when no administrative consequences were present. Additionally, the FDRS was viewed as both more difficult and less fair when there was little variance in ratee performance. Likewise, Schleicher et al. (2009) also demonstrated that in comparison to traditional rating scales, FDRS methods received less favorable difficulty and fairness ratings, both of which were related to rater confidence in conducting performance evaluations and rater selfefficacy for use of the FDRS. Given the mixed reception that FDRSs have received both in the popular press and in the research literature, personnel managers may be left wondering whether they should use this technique in their organizations. One key piece of information that is missing among the available literature, however, is the impact of an FDRS on AI. Thus, we examined in the current study the relationship between an FDRS used for the purpose of layoffs and subsequent AI. Legal Issues in PA As a personnel practice, PA is covered by the Uniform Guidelines (Equaly Employment Opportunity Commission [EEOC], 1978). These guidelines apply to “tests and other procedures which are used as a basis for any employee decisions” (p. 201). One critical case that helped to establish the coverage of PAs under the Guidelines was Brito v. Zia Company (1973). In this case, the Tenth Circuit Court of Appeals found that PAs are considered tests and are subject to the guidelines enforced by the EEOC. Therefore, PA methods are subject to legal scrutiny when they are used in any employment decisions. As PA instruments are used to make a number of employment decisions i…