هوش هیجانی : بررسی فرا تحلیلی اعتبار پیش بین و شبکه وابسته به قانون

This study used meta-analytic techniques to examine the relationship between emotional intelligence (EI) and performance outcomes. A total of 69 independent studies were located that reported correlations between EI and performance or other variables such as general mental ability (GMA) and the Big Five factors of personality. Results indicated that, across criteria, EI had an operational validity of .23 (k=59, N=9522). Various moderating influences such as the EI measure used, dimensions of EI, scoring method and criterion were evaluated. EI correlated .22 with general mental ability (k=19, N=4158) and .23 (Agreeableness and Openness to Experience; k=14, N=3306) to .34 (Extraversion; k=19, N=3718) with the Big Five factors of personality. Results of various subgroup analyses are presented and implications and future directions are provided.

Research on emotional intelligence is gaining momentum (cf. Davies, Stankov, & Roberts, 1998; Goleman, 1995; *Mayer, Caruso, & Salovey, 1999) and becoming one of the most topical areas in organizational research. To some extent, this recent emphasis on emotional intelligence arises from the renewed interest in personality research (cf. Barrick & Mount, 1991; Hough & Ones, 2001). This article discusses the current state of affairs in emotional intelligence research and then applies meta-analytic procedures to provide the first comprehensive understanding of the power of EI to predict performance outcomes. The article also explores the nomological net of EI with other individual difference variables that psychologists traditionally use to predict behavior: General Mental Ability (GMA) and the Big Five factors of personality. It is difficult to provide an operational definition of EI that is accepted by all. This is not surprising as decades of research on stress, for example, still has not resulted in a universally accepted definition of what constitutes stress; the same can be said of the research on GMA as well as the definition of personality variables (cf. Goldstein, Zedeck, & Goldstein, 2002; Ones, 1993; Ones & Anderson, 2002). The EI concept is typically credited to Salovey and Mayer (1990) who coined the term emotional intelligence but Thorndike (1920) first proposed the idea of social intelligence that some consider akin to EI (but see Mayer & Salovey, 1997). In actuality, EI can best be thought of as a subset of social intelligence (Salovey & Mayer, 1990). However, since the construct of social intelligence is broader than EI, it has often been difficult to discriminate between it and GMA. As a more isolated construct, EI may be more distinct from GMA and personality. In addition, it is possible that measures of EI, especially ability based, are less susceptible to faking than other measures that are more transparent. Nonetheless, others (Kaufman & Kaufman, 2001) argue that the origins of EI can be traced to Binet’s early notions of intelligence. Gardner (1993) has postulated that social intelligence consists of a person’s inter- and intra personal intelligences. Still, EI was not truly popularized until the recent renaissance of the dispositional approach in the workplace (cf. Hough & Ones, 2001). The differing names given to emotional intelligence are part of the reason that it has been difficult for researchers to agree on an all-encompassing definition. Emotional intelligence has also been referred to as emotional literacy, the emotional quotient, personal intelligence, social intelligence, and interpersonal intelligence (Dulewicz & Higgs, 2000). The definitions are so varied, and the field is growing so rapidly, that researchers are constantly amending even their own definitions of the construct. Nonetheless, although the definitions of EI vary, they tend to be complementary rather than contradictory (*Ciarrochi, Chan, & Caputi, 2000). Based on the many definitions that have already been proffered, this article conceptualizes EI as the set of abilities (verbal and nonverbal) that enable a person to generate, recognize, express, understand, and evaluate their own, and others, emotions in order to guide thinking and action that successfully cope with environmental demands and pressures.

Results of the current meta-analysis demonstrate that emotional intelligence is a construct that is definitely worthy of future research and indicates that EI should indeed be considered a valuable predictor of performance. Although the correlation between EI and performance (ρ=.23) is not as high as many have claimed or would like, it is considerably higher than other selection methods (e.g., letters of reference) that are commonly used. The overall predictive validity of EI appears to hold fairly constant across all performance domains. The correlations ranged from a high of ρ=.24 for work performance and the group classified as other outcome variables to .10 for academic performance. The current findings should therefore generalize to many different outcomes. Additionally, since the meta-analysis drew from a representative sample consisting of many different countries and occupations, the results should also generalize across populations. Our results also indicate that emotional intelligence and personality appear to be more highly correlated than many researchers would prefer. Indeed, three of the Big Five factors of personality had correlations with EI in excess of .31; the lowest correlation was .23 with agreeableness and openness to experience. This suggests that the distinctiveness of EI and personality may not be as clear-cut as it needs to be. Future measures will have to address this issue, and construct measures of EI that are not as highly correlated with personality. However, EI did show incremental validity over the Big Five; the Big Five did not demonstrate incremental validity over EI. Thus, it is possible that EI could be considered a better predictor of performance than the Big Five factors of personality. In light of this finding, more research now needs to address potential group differences in EI in order to ascertain that no adverse impact exists. The relationship between EI and GMA is considerably stronger when looking at only the ability based MEIS in comparison to the other models that do not suggest a relationship between EI and GMA. Since the correlation (.33) of the ability based MEIS with GMA is so much higher than the other measures (.09), it is likely that two different constructs are in fact actually being measured. Finally, unlike with personality, EI did not evidence incremental validity over GMA. However, GMA did significantly predict performance beyond that explained by EI. Thus, the claims that EI can be a more important predictor than cognitive ability (e.g., Goleman, 1995) are apparently more rhetoric than fact. The issue of emotional intelligence is relatively new, but the concept of emotions at work has been around for sometime now. Unfortunately, emotions and work has been an understudied area. This is a mistake as emotions are common at work and it would be futile to continue to ignore the role of emotions in the workforce (Arvey et al., 1998). However, of all the work on emotions and work, the research on EI is possibly the one with the most dual interest to academics and practitioners alike and the number of studies, conferences, and publications on this topic is increasing at a rapid pace (Ashkanasy & Daus, 2002). Knowledge of emotions or EI can only help in providing us with a better understanding of workplace performance. Thus, our meta-analysis comes at a critical time and it provides information that will enable researchers to further develop the field of EI. More specifically, researchers need to more laboriously examine the influence of EI at work. This will involve more tests of its predictive validity, tests on how EI can be taught and learned, and how EI affects the worker at an individual, team, and organizational level. Further, although our meta-analytic results suggest robust predictive validity for EI measures for assessing performance in employment settings, researchers have focused on a narrow set of criterion variables. Hypotheses have been postulated that effective emotional regulation will reduce the potential for burnout (cf. Grandey, 2000). If so, emotional intelligence should be a predictor of burnout, and perhaps may even function as moderator in that individuals high on EI may be better able to buffer the effects of burnout. The role of emotions in the workplace was probably first underscored by Hochschild (1983) who studied the effects of emotional labor in service industries. The growth of the service industry in the recent decades enhances the role of emotional intelligence in the workplace (Rafaeli, 1989; Rafaeli & Sutton, 1987). Demonstrating that EI measures predict job performance is only the first step and should spur researchers to investigate how job characteristics moderate the display and deciphering of emotions. Also, the changing nature of the workplace (Howard, 1995) has a dual effect on the importance of emotional intelligence in the workplace. On one hand, telecommuting and other technological advances minimize human interaction and thereby reduce the importance of EI. Alternately, the same technological advances make the perception, understanding, assimilation and management of emotions in the self and others more critical for success; what is true of the workplace is true of the society at large. In a time of frequent downsizing and continuous restructuring, emotions are a critical component of success. The emotionally intelligent worker is more likely to succeed in such a work environment. Additionally, with the increasingly diverse workplace demographics, EI can increasingly benefit a worker. Beyond helping the worker as an individual, EI should also help the work team as a whole. The emotionally intelligent person is more likely to empathize with others and find ways to work together productively. This provides a number of other implications for individuals and organizations. First, if EI is truly a valuable predictor of performance, it would be wise for individuals to better understand their own, and others, emotions. Similarly, organizations could realize significant cost savings and profit improvements if EI could be improved. Accordingly, future research should address the extent to which EI can be improved over time through training and, possibly, introspection. This should be of interest to individuals such as career counselors who are constantly exploring new ways of raising individual performance. Career development has gained a prominent role in organizations given the rapid changes taking place in organizations and EI is likely to be an important construct in career development initiatives. However, considering our results, any potential development of EI may depend on which model of EI is used. In other words, the ability models, which are related to GMA, may indicate that more development can occur than the mixed models of EI. Expatriate workers are another group who may need to possess elevated levels of EI in order to be successful. The expatriate worker faces an entirely different set of circumstances and if the person is in touch with their own, and others, feelings they are going to have a better transition and be more successful. It could be argued that the current meta-analysis drew extensively from studies that were not published in top tier journals. While this may be true, the quality of many of the studies, such as the dissertations, should not be understated (Ones, 1993). Additionally, the inclusion of unpublished studies may result in a more accurate measure of the true validity of a predictor. Published studies may tend to overly inflate the true correlation as only significant results are typically published thereby omitting relevant studies that should not be overlooked in a quality meta-analysis (i.e., the file drawer problem). Our results may then present a more accurate representation of the true validity of EI since less upward bias should exist given that all available studies on EI were included. An additional concern could address the issue of correcting for reliability using reliability values that were listed in the original measure and not in the study of interest; this correction was only made if multiple studies were placed within one document (e.g., technical manual). However, a similar issue has already been raised and acknowledged previously. It was recommended that correcting for unreliability using estimates from a study other than the current one is better than the additional bias that would result from not using any estimates (Viswesvaran, 2002). Further, the subgroup hypotheses tested where in some instances omnibus in nature in that we did not specify the direction of the expected differences. However, our exploratory analyses are informative in summarizing the extant literature and, along with other directional hypotheses, guide our understanding of this new and important construct. Future research should explore our subgroups more thoroughly and investigate the effects of correlated moderators in a fully hierarchical moderator analysis once more studies have been completed (Hunter & Schmidt, 1990). Finally, whereas Q-statistics and confidence intervals can be used to test the statistical significance of different subgroups, we chose to be liberal in our estimation of subgroup effects in this paper. Thus, we discuss correlational differences even when they are not statistically significant because we believe that one meta-analysis (however great) is not definitive enough to rule out areas of potential research. Interested readers can use the information provided in our Tables to draw stronger conclusions based on professional knowledge and risk-taking proclivities. Our objective was to summarize the scattered extant literature in one place and draw inferences that are justified in our professional judgment (not necessarily based on statistical significance). Finally, there may be some researchers who would question our use of the Big Five personality factors when assessing incremental validity. It could be argued that this takes too narrow of a view of personality and that the values of Barrick and Mount (1991) are not the most accurate. However, Barrick and Mount are the most highly cited personality article in the last decade and so we considered their values to be a good starting point. One weakness with the existing EI research can be traced to the classification, measurement, and validation of the sub-dimensions that are used. The current measures typically use either the 4- or 5-dimension model but continued research is needed to explore which dimensions are actually necessary. Because the two different models are derived from a different conceptual framework, we are not recommending that one model needs to be discarded at this point. Instead, it is recommended that the dimensions continue to undergo refinement. Additionally, since the four-dimension model is proposed as a hierarchy, longitudinal research is needed to address the issue. This may not be an easy task, but it is undoubtedly a necessary step that needs to be taken in the refinement effort. To the extent that the four dimensions of emotional intelligence can be causally (or at least temporally) ordered, one can expect differential relationships between the dimensions and performance (i.e., dimensions that are more temporally antecedent to performance are expected to have stronger relationship). However, to the extent progressive range restriction occurs the results would be opposite. Our subgroup analyses were designed to explore the competing possibilities. The results of this study, for instance, indicate a weak relationship between the perception of emotion dimension and performance. Longitudinal research will allow for a closer examination of this and it may indicate that certain dimensions could be eliminated or combined. The results of the meta-analyses reported here also have implications for refining the construct of EI and for constructing new measures. For instance, no research to date has evaluated the extent that measures of EI assess typical or maximal performance. It still needs to be determined if measures of EI gauge what a person can do or what they will do. In other words, are these measures assessing how people perceive, interpret, and understand emotions during the course of everyday life or only when they are thinking deeply about their emotions (such as when they take the measure)? Future research should also address the possibility of faking these measures. More importantly, many of the measures of EI developed so far have not clearly articulated the theoretical framework guiding their item construction nor have the strategies used for item selection, for inclusion in the final measure, been clearly delineated. For example, emotions have been conceptualized as cognitive interpretations, physiological processes, and social constructions. It needs to be shown that the existing measures of EI are applicable for all the different conceptualizations of emotions. Further, researchers have debated the dimensionality of emotions as comprised of either two or three dimensions—valence, arousal, and potency (Russell, 1991). This raises questions such as: (1) When we assess emotional intelligence what dimension is focused on? (2) Are the different measures of EI tapping into the same dimension of emotion? Furthermore, when we talk of dimensions of EI such as perception, understanding, assimilation, management of emotions, are these dimensions of EI the same for all types of emotions (e.g., shame, guilt, etc.)? Psychologists have spent many decades studying each of these emotions separately, and it would be a noteworthy conclusion if the same intelligence processes underlie these different literatures. Although most of the literature is on negative emotions, recently there has been an emphasis on positive psychology (Seligman, 1990). The construction of new measures, and the refinement of existing ones, will be greatly facilitated by such an integrative framework. On a related note, one could also inquire as to whether the measures are domain-specific or more generalizable. Our subgroup analyses across academic, employment and life outcomes suggest that the assessment of emotional intelligence is indeed applicable in different domains. One of the subgroups analyzed in this paper found that scoring self-reports with expert ratings resulted in higher predictive validities than scoring using group consensus ratings. Perhaps experts were able to decipher the content of the items more accurately than the group. However, the meaning and appropriate inferences of emotions have evolved over time (Mastenbroek, 2000). Thus, there is potential for cultural differences in perception and management of emotions. Unless expert ratings are based on a representative sample of experts from all different cultures assessed, the superiority of expert ratings over consensus ratings for scoring self-reports may not be generalizable to new settings. The current meta-analysis is an important addition to the field of EI research for a number of reasons. First, as mentioned, in addition to using published research, the current meta-analysis also combined the results of many EI studies (e.g., theses, technical reports) that are often difficult to find and obtain. Second, the results of the meta-analyses presented here not only provides the relationship between EI and performance, it also tests many subgroups that could act as potential moderators. An examination of these coefficients and results will be beneficial, and can act as a guide, for future EI research and refinement efforts. Additionally, the current results indicate that approximately 4% of the variance in performance can be explained by EI; for work performance this figure is closer to 5%. This may not seem like a significant percentage, nor is it in line with claims of some EI researchers who have posited that EI may be more important than IQ, but it is large enough to generate significant savings and improvements for organizations that use measures of EI. Finally, we also summarized the correlation between measures of EI and other constructs such as GMA and the Big Five factors of personality. Oftentimes, it is difficult to estimate the intercorrelations across different variables, which hinder the development of a nomological net, and to address questions of incremental validity (Bobko, Roth, & Potosky, 1999; Cortina, Goldstein, Payne, Davison, & Gilliland, 2000; Schmitt, Rogers, Chan, Sheppard, & Jennings, 1997). In summary, the current meta-analysis has provided a more accurate estimate of the predictive power of EI than was previously available. Additionally, construct validity in terms of correlations with GMA and the Big Five factors of personality was summarized. Future research should build on these findings to develop more refined measures of the construct as well as investigating the full potential of the EI concept.