This study investigates the relationship between emotional intelligence (EI) and Total Sales Performance (TSP), and whether EI contributes to predicting the performance of sales professionals in Kuwait. The sample was 218 sales professionals working for 24 different car dealerships. An ability model of EI was measured using the Assessing Emotions Scale (AES) developed by Schutte et al. (1998) and its Arabic version. The trait model of EI was assessed using the Effective Intelligence Scale (EIS). The findings showed a negative but weak correlation between TSP and the AES and all its subscales. No correlation was found between TSP and the EIS. A weak positive correlation existed between Objective Sales Performance and each of total EIS, Accuracy, and Patience subscales.
Este estudio indaga en la relación entre inteligencia emocional (IE) y productividad en el total de ventas (PTV) y si la primera contribuye a predecir la actuación de los comerciales profesionales en Kuwait. La muestra estaba compuesta por 218 comerciales profesionales que trabajaban en 24 concesionarios diferentes de automóviles. Se siguió el modelo de habilidades de inteligencia emocional, utilizándose la versión árabe de la Escala de Evaluación de Emociones (EEE) de Schutte et al. (1998). La IE de rasgo se evaluó mediante la Escala de Inteligencia Eficaz (EIE). Los resultados indican una correlación negativa débil entre PTV y la EEE y todas sus subescalas. No se obtuvo correlación entre PTV y EIE. Se dio una correlación positiva débil entre ventas objetivas y cada una de las subescalas del EIE, precisión y paciencia.
Emotional Intelligence (EI) continues to receive considerable attention from researchers in the fields of psychology, organizational behavior, and human resource management. Salovey and Mayer (1990) defined EI as “the ability to understand emotions and feelings in oneself and others and to use this understanding as a way to direct actions”. Specifically, they postulated that EI consists of three abilities: (1) appraisal and expression of emotions, (2) regulation of emotions, and (3) utilization of emotions. They proposed that EI is a newly classified type of intelligence and that it affects job performance.
Recent research indicates that interpersonal and intrapersonal intelligence, two key components of EI, may be more essential to success in life than IQ (Cooper & Sawaf, 1997; Mayer & Salovey, 1995, 1997; Salovey & Mayer, 1990; Weisinger, 1998). Unlike IQ, which is considered to be relatively stable and unchangeable, EI skills can be improved through learning and practice (Goleman, 1998). These studies and others have encouraged researchers to investigate the relationship between EI and success at work, defined as the degree to which an individual helps the organization reach its goals (Motowidlo, Borman, & Schmit, 1997).
Rooy and Viswesvaran (2004) conducted the first meta-analytic study to provide a comprehensive understanding of EI's power to predict performance outcomes. The study assessed the overall influence of EI on performance. Results indicated that, across criterion domains (employment, academic, and life), emotional intelligence had an overall operational validity of .23 as examined across 59 independent samples involving 9,522 participants. The results revealed that EI measures have predictive validity in most situations but that the exact magnitude varies by situation. EI measures have an operational validity of .24, 0.1, and .24 for predicting performance in employment, academic, and life settings, respectively. Moreover, the meta-analysis examined the performance criterion measurement method as another moderator of the predictive validities. The study analyzed two criteria: (1) organizational records and (2) ratings. The use of ratings criteria yielded a higher operational validity compared to the use of organizational records (.26 and .14, respectively). Supervisor and self-ratings had comparable validities (.25 and .27, respectively).
In a recent meta-analysis, O’Boyle, Humphrey, Pollack, Hawver, and Story (2011) investigated whether EI measures incrementally predict job performance when measures of personality and cognitive ability are also used as predictors. Their meta-analysis included the three main streams of EI measures available in the literature, namely, (1) ability-based measures defined in Mayer and Salovey (1997), (2) self-report measures based on the Mayer-Salovey model, and (3) measures that go beyond the Mayer-Salovey definition. The researchers found that the three streams have corrected correlations ranging from .24 to .30 with job performance and that they correlated differently with cognitive ability and with neuroticism, extraversion, openness, agreeableness, and conscientiousness. Streams 2 and 3 have the largest incremental validity beyond cognitive ability and the Five Factor Model (FFM). Using dominance analysis, they found that the three streams of EI exhibited substantial relative importance in the presence of FFM and intelligence when predicting job performance. They concluded that the results support the overall validity of EI. The researchers found that the overall relation between EI and job performance is positive and significant, that the three streams of EI relate to job performance at similar levels, and that no significant differences exist between the streams. The data strongly supported the predictive validity of EI in terms of job performance, and was higher than the influence of personality and cognitive ability.
However, Cote, Christopher, and Miners (2006) found that while EI is a predictor of job performance, it does not have a linear effect. They found that EI becomes a stronger predictor of task performance as cognitive intelligence decreases, which supports their argument that a compensatory model exists in which cognitive intelligence moderates the association between EI and job performance.
Sales personnel work in an environment where social and emotional skills are of importance. Their performance is related to their ability to manage social and emotional problems and to maintain high level of motivation to face problems arising due to negative feedback and failures (Brown, Cron, & Slocum, 1997). A salesperson high in EI should be resilient and able to handle the emotionally threatening consequences of failure which is common in the life of the salesperson. In-depth interviews with high performing salespeople conducted by Deeter-Schmelz and Sojka (2003) revealed that these workers often and unknowingly used EI to be effective. These salespeople, for example, all reported using the ability to empathize with customers, and some indicated the importance of putting themselves in their customers’ shoes. They also understood the importance of perceiving others’ emotions, which influenced how they adapted their approach to specific customers and sales calls. Self-awareness was also seen as important in influencing the impression they created with the customers. The ability to control their emotions, i.e., self-regulation, was seen as important in keeping them focused on key issues and working to resolve customers’ problems.
Studies conducted specifically with salespeople found that EI is positively related to sales revenues. Kidwell, Hardesty, Murtha, and Sheng (2011) found that real estate and insurance salespeople with higher EI generate higher annual sales revenue and are better at retaining customers. Moreover, Jennings and Palmer (2007) reported improvements in sales revenue resulting from EI development in a large pharmaceutical company. The EI and sales revenue of participants were measured before and after the program and were compared to a control group that was given no development. Participants’ EI improved by a mean of 18% while the control group's EI decreased by 4%. Additionally, the total sales revenue of the participants was found to increase by an average of 12% compared to the control group. The enhanced sales results were not simply a result of market influences.
While the above mentioned studies provide evidence that EI is a predictor of job performance, one study conducted specifically with car salespeople found no relationship. Bryant (2005) used Multifactor Emotional Intelligence Scale (MSCEIT v2) with car and consulting services salespeople from 17 automotive retail stores in Denver, Colorado, and found no relationship between EI and objective sales performance.
There is a fair amount of research on emotional intelligence and studies on sales performance, but not in the car sales arena. Thus, the present study attempts to address this knowledge gap. Moreover, the issue of sales performance within Kuwait has not been examined in any internationally published research. Accordingly, the present study was undertaken to explore these issues. The researchers have selected the automotive industry as the work environment to examine. Kuwait has a small population of 3,065,850 as per the Kuwait Central Statistical Bureau (2011). However, it has one of the highest rates of cars per 1,000 people, reaching 439 in 2010 (vs. 403 in 2008 and 412 in 2009), as per the World Bank (2013). The automobile trade is among Kuwait's most prosperous commercial activities. As the automotive industry contributes significantly to Kuwait's economy and culture, the sales activity within this industry is worth investigating. The stimulant factors of sales performance are a focus of many HRM, psychology, and organizational behavior researchers seeking to optimize performance. One such stimulant is EI.
In this study, the AES scale was used to assess Emotional Intelligence. This scale was developed by Schutte et al. (1998) with participants from the United States. Upon review of the scale by Schutte, Malouff, and Bhullar (2009), the researchers reported that AES scale was used in several studies, mainly in English speaking countries including Canada, Australia, Polland, and Malaysia. The scale was found to have good psychometric properties. Therefore, conducting a study about EI in Kuwait using this scale is an opportunity to experiment its psychometric properties in an Arabic culture. Not all scales developed in Western countries are necessarily applicable in Eastern ones. Cultural factors might affect the perception of scale items, and hence its psychometric properties. However, this study showed good scale properties.
This study was concerned with unleashing factors fundamental to successful sales performance in the automobile industry in Kuwait. Kuwait has one of the highest figures per capita automobiles reaching 439 in year 2010 (vs. 403 in year 2008, and 412 in year 2009), as per The World Bank (2013). And the fact that 30 car dealerships operate in this competitive market means working in the cars sales is a challenging job. From a human resource management point of view, this makes the recruitment very selective. It is reflected in the sample of this study, which was found to have high levels of average sales performance, which limited the variance within it. Therefore, conducting a study in this setting is valuable in understanding how EI would contribute to sales performance of highly competent salespeople.
Moreover, a majority of expatriates characterized the sample in this study. Kuwaiti citizens do not usually occupy full time sales profession. Therefore, this study revealed, indirectly, how expatriates would perform in their jobs, which will be reflected on the organization performance as well. This might be of interest to industries and/or countries that have expatriates occupying certain professions and how HRM practices would develop mutual benefits.
The objective of this research is to explore the relationship between EI and performance of sales executives working in Kuwait's automotive industry. This study addresses four main research questions: What is the relationship between EI and Total Sales Performance (TSP)? What is the relationship between EI and Objective Sales Performance (OSP)? Can EI be a predictor of sales performance? And does EI vary with the demographic factors of salespeople, namely age, years of experience in the current company, and overall years of experience in sales?
Automobile sales organizations hire sales representatives to generate revenue and achieve sales goals. If management could screen sales representatives and predict sales performance success by EI scores, the automobile sales organizations could be more successful. Previous research reveals that high EI can be an indicator of career success (Cote et al., 2006; Heffernan, O’Neill, Travaglione, & Droulers, 2008; Morehouse, 2007). If the results of this study agree with those of previous studies, then sales managers might consider implementing strategies that develop their sales employees’ EI in order to achieve optimum sales performance and compete for greater market share. Weinberger (2002) proposes that if such a relationship exist, then future research could look at the predictive power of whether this ability can be effectively trained and developed in others. Also, sales organizations can be in a better position to develop a strategic plan as it pertains to hiring, training, increasing sales, and retaining talent.
MethodSampleThe target sample consisted of sales professionals working in the Kuwait automotive industry. The researchers met with and submitted formal proposals to managers of all 30 car dealerships in Kuwait. Twenty-four managers (80% of those approached) agreed to participate, resulting in a total of 218 sales employees who participated in this study. All participants sold cars or related services. The majority of workers were sales executives (74.8%); other titles included sales team leader (0.9%), sales manager (0.9%), service advisor (8.3%), and parts sales officer (15.1%). The nationalities were mixed: Lebanese (28.9%), Indian (20.2%), Egyptian (14.2%), Jordanian (13.3%), Syrian (6.4%), Pakistani (3.7%), Kuwaiti (2.3%), Iraqi (2.3%), Iranian (2.3%), Palestinian (1.8%), Sri Lankan (1.4%), Tunisian (0.9%), Filipino (0.9%), Yemani (0.5%), Moroccan (0.5%), and Canadian (0.5%). The majority of participants were male (95.4%). They had worked an average of 6.8 years (SD=6.63) with their current employers and had an average of 12.5 years (SD=7.34) of sales experience. The average age of the participants was 37 years (SD=8.69). Most were married and educated with a university degree.
MeasuresAssessing Emotions Scale (AES). Originally developed by Schutte et al. (1998), this measure is a self-report scale based on the ability model of EI developed by Salovey and Mayer (1990). The AES is composed of three dimensions: Appraisal and Expression, Self-Regulation, and Utilization of Emotions. It consists of 33 items, with 11 items for each dimension.
This study used the Arabic version of the AES derived by Mousa (2004). Researchers extended the Likert scale of responses from 4 to 5 points. Thus, responses are rated from 1 (totally disagree) to 5 (totally agree). The lowest attainable score is 33, and the maximum score is 165. Mousa (2004) reported the reliability (Cronbach's alpha) of the scale to be .9 with the reliability of its dimensions as follows: Appraisal and Expression .79, Regulation of Emotion .79, and Utilization of Emotions .81. The reliability of the measure in this study was found to be .84. Mousa also reported the internal consistency, discriminant validity, trustee validity, and content validity of the scale. Moreover, this measure correlated .66 with the Effective Intelligence Scale, the other measure used in this study to assess EI. Both the Arabic and the English versions of the measures were used; 156 participants completed the Arabic version, while the other 62 completed the English version. We were unable to assess the correlation between the two versions, as most participants were fluent in one language only.
The researchers did not include measures of personality or cognitive intelligence in this study. However, several studies have examined the relationship between scores on the AES and the Big Five dimensions of personality. Schutte et al. (1998), Bracket & Mayer (2003), and Bastian, Burns, and Nettelbeck (2005), respectively reported the following correlations between the AES and each of the Big Five dimensions: extraversion, .28, .32, .61; agreeableness, .26, .09, .23; conscientiousness, .21, .25, .32; emotional stability, .28, .19, .37; and openness, .54, .43, .43. These correlations indicate that across study scores on the AES are relatively distinct from scores on each of the Big Five dimensions. Openness had the highest average association with the AES, .47, indicating shared variance (r squared) of approximately 22%.
Additionally, in their first study titled “Development and Validation of a Measure of Emotional Intelligence”, Schutte et al. (1998) tested the discriminant validity of the AES versus a cognitive ability test (SAT test). Scores on the 33-item measure of AES were not related to SAT scores, r(41)=-.06.
The Effective Intelligence Scale (EIS). The scale, developed by Mansour, Yousef, and AlShafei (2001), is based on the work of Al-Aser (1998), which adapts Goleman's (1995, 1998) model of EI. The EIS is a self-report scale consisting of 27 items, after excluding the six dispersion items. The scale measures five dimensions: Accuracy, Patience, Optimism, Effective Dealing with Self, and Dealing with Others. The scale is rated according to the 5-point Likert scale from 1 (totally disagree) to 5 (totally agree). Mansour et al. (2001) reported the reliability of the scale to be .79, while the reliability of its dimensions as follows: Accuracy .72; Patience .82, Optimism .72, Dealing with Self .79, and Dealing with Others .78. The content validity is also reported. The concurrent validity of the EIS with the Assessing Emotions Scale was found to be .66. Almazroa (2007) found that EIS correlates .45 with Self-efficacy. The reliability of this measure in this study was found to be .85.
Sales Performance Measure. Sales performance was measured using the supervisors’ evaluation of both Objective Sales Performance (OSP) and subjective work-related dimensions (Total Sales Performance, TSP). For confidentiality reasons, the car dealers were reluctant to provide us with the actual sale numbers for each salesperson. Instead, they supplied us the percentage of sales target achieved during the previous 12 months before the start of the study (OSP). The TSP has twelve items rated from 1 to 10. Yearly sales performance was used in this study. It assesses the following criteria: Self-development, Job Understanding, Initiative, Dealing with Others, General Appearance, Accuracy, Speed, Effective Use of Time, Use of Knowledge, Adherence to Rules, Confidentiality, Following Supervisors’ Orders, Relationship with Colleagues, and Adherence to Attendance Time. The Cronbach's alpha coefficient for this scale was found to be .94.
ProcedureMeeting with car dealership managers to present and explain the study took the first and second author approximately one month (April 2011). After obtaining the approvals, the first author coordinated meetings with the sales employees from each organization to collect data.
Almost all salespeople in each organization participated in this study. While distributing the EI questionnaires at each dealership, the first author intentionally did not mention anything about emotional intelligence to the salespeople to avoid altering their responses. Completion of the questionnaires took an average of thirty minutes. To measure sales performance, sales managers were given questionnaires that assessed the yearly performance of their salespeople. It took at least one month for sales managers to complete and return the performance questionnaires. The entire data collection process started in May 2011 and ended in March 2012 partly because the entire population of car dealers in Kuwait was included in this study, and partly because of the challenges of coordinating thorough follow-up meetings with the very busy schedules of the dealerships.
Then, the data were entered by the first author using the SPSS (Statistical Package for the Social Sciences) software package and were reviewed three times before starting the analysis. As part of the SPSS analysis, the Kolmogorov-Smirnov test for normality was employed. The test revealed that the normality assumption is valid for all scale dimensions. The other types of SPSS analysis are given in the results section below.
ResultsTable 1 shows descriptive statistics and reliability coefficients for all measures. The total EIS, AES, and Sale's Performance measures have high Cronbach alpha coefficients, where the sub-measures of AES have reasonable coefficients. The means and standard deviations are shown in Table 1.
Descriptive Statistics and Reliability Coefficients for All Measures.
| Scales and Subscales | M | SD | Chronbach's alpha |
|---|---|---|---|
| Self-evaluation | 45.41 | 4.60 | .64 |
| Self-regulation | 44.69 | 4.71 | .64 |
| Utilization of emotion | 45.37 | 4.80 | .69 |
| AES Total | 135.47 | 12.07 | .84 |
| Accuracy | 21.67 | 2.65 | |
| Patience | 23.92 | 3.25 | |
| Optimism | 25.33 | 3.16 | |
| Dealing with self | 21.03 | 2.41 | |
| Dealing with others | 20.49 | 2.94 | |
| EIS Total | 112.44 | 11.07 | .85 |
| TSP | 91.94 | 16.78 | .94 |
| OSP | 77.00 | 19.30 |
Note. AES=Assessing Emotions Scale; EIS=Effective Intelligence Scale; TSP=Total Sales Performance; OSP=Objective Sales Performance.
As shown in Table 2, we found a negative weak but significant correlation between TSP and AES (r=-.16), and its subscales Self-Evaluation (r=-.15), Self-Regulation (r=-.13), and Utilizing of Emotions (r=-.12). However, no significant relationship was found between TSP and the EIS. Additionally, no significant relationship was found between OSP and AES. Moreover, a positive weak but significant correlation was found between OSP and the EIS (r=.12) and its subscales: Accuracy (r=.16) and Patience (r=.12). Similarly, OYES in the sales field correlated significantly but weakly with both AES (r=.12) and EIS (r=.13).
Intercorrelation Matrix between Measures.
| Category | N | AES | EIS | TSP | OSP | Age | YECC | OYES | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Self-evaluation | Self-regulation | Utilization of emotions | Total AES | Accuracy | Patience | Optimism | Dealing with self | Dealing with others | Total EIS | |||||||
| TSP | 201 | -.15* | -.13* | -.12* | -.16* | .08 | -.02 | -.05 | -.03 | -.05 | -.02 | |||||
| OSP | 203 | .02 | .08 | .04 | .06 | .16* | .12* | .01 | .11 | .08 | .12* | .45** | ||||
| Age | 218 | .13* | .05 | .04 | .08 | .10 | .01 | .05 | .15* | .07 | .09 | -.03 | .02 | |||
| YECC | 218 | .14* | .03 | .06 | .09 | .09 | .01 | -.05 | .10 | .03 | .04 | -.05 | .07 | .66** | ||
| OYES | 218 | .10 | .01 | .05 | .12* | .12* | .08 | .09 | .16** | .07 | .13* | -.07 | -.02 | .82** | .73** | |
Note. AES=Assessing Emotions Scale; EIS=Effective Intelligence Scale; TSP=Total Sales Performance; OSP=Objective Sale Performance; YECC=Years Experience in Current Company; OYES=Overall Years’ Experience in Sales.
Linear regression, as shown in Table 3, was used to investigate the effect of the independent variables satisfying the regression equation (AES, EIS, age, experience within current company, and overall experience in the sales field) on the dependent variable (TSP). Note that another regression equation revealed no effect of any of the independent variables on OSP.
Regression Coefficients.
| Predictive Variables | R | R2 | F | B | Beta | t | Sig. |
|---|---|---|---|---|---|---|---|
| Constant | .289 | .083 | 3.55** | 126.530 | 8.433 | .000 | |
| AES | -0.338 | -.240 | -2.632 | .009 | |||
| EIS | 0.178 | .117 | 1.284 | .201 | |||
| Age (years) | -0.480 | -.246 | -2.018 | .045 | |||
| YECC | -0.454 | -.179 | -1.760 | .080 | |||
| OYES | 0.954 | .416 | 3.118 | .002 |
Note. AES=Assessing Emotions Scale; EIS=Effective Intelligence Scale; YECC=Years of Experience in Current Company; OYES=Overall Years Experience in Sales.
The F-value for variance was found to be statistically significant at p=.01, where R was found to be .289. The equation demonstrates that the AES scale is inversely predictive of TSP. However, Total EIS was found to not be predictive of TSP. Notably, this finding was not consistent with the result of correlation analysis. As it did not satisfy the regression equation, the researchers will rely on the regression findings. Age was found to be inversely predictive of TSP, i.e., the younger the salesperson, the higher his/her TSP, while Years of Experience in the Current Company was found to not be predictive of TSP, the Overall Experience in Sales Field was. The regression equation shows that Overall Experience in Sales Field, Age, and AES collectively contribute by 8% to the variance among sales employees in TSP.
DiscussionThe sample was characterized by high sales performance levels, both total and objective. The automotive industry in Kuwait has one key purpose: to sell cars with more than 30 different brands competing in a small market. Because the competitive nature of this industry demands highly competent sales employees, this sample population is selective. Additionally, the sales employees studied receive effective training in professional selling skills, which was reported by their supervisors and HR departments and is reflected in the results.
However, previous research in sales found that self-reported and managerial-reported performance data are positively skewed (Dwyer, Hill, & Martin, 2000; Sharma, Rich, & Levy 2004). Both objective and subjective managerial-reported performance data were used in this study. Both criteria were used because it has been found in multiple meta-analyses of job performance that the two types are non-exchangeable (Bommer, Jonathan, Gregory, Philip, & Scott, 1995; Ng, Eby, Sorensen, & Feldman, 2005). Although objective data (actual sales volume achieved) is not subject to bias by the rater (sales manager), in this research no significant relationship was found between OSP and emotional intelligence assessed by AES, whereas TSP was found to be significantly correlated with AES.
In the meta-analysis conducted by Rooy and Viswesvaran (2004) to assess the influence of emotional intelligence on performance, they found a positive correlation between EI and work performance but the magnitude is not strong, r=.24. Also, in the recent meta-analysis of O’Boyle et al. (2011) they found the three streams of EI measures reported in the literature do have significant positive correlations with job performance, but the magnitude is not strong, ranging from r=.24 to .30.
In this study, the researchers included the entire population of car sellers in Kuwait and as mentioned in the results section they found the sample to be characterized by a high mean EI level on the AES scale. Moreover, the variance within the sample was found to be low, i.e., the variation in the dependent variable (sales performance) was low. This might have contributed to the inability to unveil a relationship with the independent variable (EI), especially that our model hypothesized a linear relationship between EI and performance.
Interestingly, when the data was divided to “high” and “low” performance with reference to mean sales performance, the researchers found “low” performers to be of higher EI levels while “high” performers had lower EI levels. This is probably suggesting a non-linear relationship.
Other studies have investigated the relationship between EI and work performance using non-linear models. For example Cote et al. (2006) found the relationship to be compensatory, where EI is higher in individuals having lower cognitive intelligence in a sample of university employees, while Kidwell et al. (2011) found the relationship to be complementary, such that EI was higher among individuals with higher cognitive intelligence in a sample of sales employees. These two studies revealed that cognitive intelligence is a moderator in the relationship between EI and performance. However, in the current study the researchers have not investigated cognitive intelligence.
It is worth noting that Sturman (2003), in a meta-analysis study, searched for the inverted U-shaped relationship between time and performance. Sturman found an inverted U-shaped relationship between time and performance for the three relationships examined (job experience/performance, age/performance, and tenure/performance) in low complexity jobs. When jobs are of high complexity, the relationship is found non-linear but not an inverted U-shape. The results were the same whether the performance was measured subjectively or objectively. This paper showed how job context is a moderating factor altering the performance relationship and although it did not include EI in the study, what matters here is the job context. Selling in general is not a simple type of job, and when it comes to selling cars it is challenging for two reasons. First, a car is not a commodity and the prices are quite expensive. Second, the Kuwaiti market is small in terms of population and having 30 dealers competing makes selling cars a real challenge. So, probably “car selling” challenge or complex nature moderated the relationship between sales performance and EI in the current study.
Our study has a value of raising a scientific question regarding the relationship between job performance (sales) and emotional intelligence, rather than giving a definite result.
A similar lack of relationship was found between MSCEIT v2 and OSP for sales volume of car sellers and consulting services (Bryant, 2005). This author recommended that future researchers investigate a broader performance model or evaluate the nature of the emotional intelligence construct at the definitional stage. Dalal (2005) demonstrated that job performance is actually composed of three facets: objective/subjective ratings, organizational citizenship behavior, and counterproductive workplace behaviors. The last two facets were not included in this study.
Contrary to what is reported in most literature, the present study found a negative relationship between AES and TSP. The regression analysis results show that among the three independent variables that satisfied the equation, the two emotional intelligence scales used in this study contributed the least (by only 24%). Similarly, Rooy and Viswesvaran (2004), in their meta-analysis of the predictive validity of emotional intelligence scales, found that general mental ability did significantly predict performance beyond that explained by EI. They concluded that the claims of EI being a more important predictor than cognitive ability (e.g., Goleman, 1995) are apparently more anecdotal than factual.
In their contemporary meta-analysis of “drivers of sales performance”, Verbeke, Dietz, and Verwaal (2011) found cognitive ability to be significantly positively related to sales performance. However, as Verbeke, Belschak, Bakker, & Dietz (2008) show, cognitive abilities should be complemented by other abilities, especially social skills, to prevent firms from only hiring “competent jerks”, which can result in dissatisfied customers.
Rooy and Viswesvaran (2004) have suggested using moderator models rather than linear models when studying the relationship between emotional intelligence and job performance. This suggestion seemingly encouraged Cote et al. (2006) to propose a moderator model in their investigation. They support the arguments of Murphy (1996) and Hough (2003), which suggest that predictors of job performance such as EI may be important in ways other than incremental linear effects. Therefore, they proposed a compensatory model in which cognitive intelligence moderates the association between EI and job performance. The results of their study revealed the existence of such a relationship. They found that EI becomes a stronger predictor of task performance as cognitive intelligence decreases: employees with low cognitive intelligence perform tasks more competently if they are emotionally intelligent. Their study included 175 full-time employees of a large public university in Canada. Notably, Schutte et al. (2009), in their review of the AES, had recommended applying moderator models when studying EI.
In their recent study, Kidwell et al. (2011) also used a moderator model while researching the relationship between EI and sales performance. The result indicated a complementary relationship between EI and cognitive ability: emotional intelligence positively influences performance at higher levels of cognitive ability. This finding is the opposite of that of Cote et al. (2006). Clearly, the emotional intelligence literature is still mixed and needs more research to obtain more definitive answers.
The sample in the present study consists almost entirely of expatriates (only 2.3% of participants were Kuwaitis). Expatriate employees need to work hard to secure their jobs and are expected to apply taught skills to prove their competency.
The self-report type of scale that was used in this study to measure emotional intelligence might be another reason for the unexpected results. Bracket, Rivers, Shiffman, Lerner, and Salovey (2006) demonstrated that the self-reported emotional intelligence scales inadequately assess EI. They found rather low associations between ability models of emotional intelligence and self-report emotional intelligence scales (r values approximately .22), indicating that the approaches yield different information about the same person (Bracket and Mayer, 2003).
An important point is that in general, self-report measures are often considered to be inadequate because people tend to report their abilities inaccurately (Paulhus, Lysy, & Yik, 1998). They also tend to filter self-reports through their self-concepts and impression management motives (Mayer, Salovey, & Caruso, 2000), which potentially encourages socially desirable responses. Kirk, Schutte, and Hine (2008) found that the AES scores were not related to social desirability responding. However, the question remains as to whether self-report scales developed based on Mayer and Salovey's (1997) ability model measure actual EI ability or what the individual thinks/believes of himself/herself.
The mixed results over 20 years of emotional intelligence literature, nurtured by the use of different scales based on different concepts, urge the researchers to undertake such differences in stride. This would yield a more definitive understanding of the components of emotional intelligence, which could redirect the research efforts and HRM practices within organizations. Our study found no relationship between the EIS and TSP. This scale as reported previously in this text is based on the mixed model of Emotional Intelligence. This result does not agree with our finding above concerning the relationship between emotional intelligence and TSP.
The correlation analysis shows no association between age and emotional intelligence measured by AES (Table 2), which is not in agreement with the literature. Several studies have reported that age is positively associated with emotional intelligence (Bar-On, 1997, 2002; Mayer, Caruso, & Salovey, 2000; Mayer, Salovey, & Caruso, 2002). Generally, the meta-analytic review of predictors of sales performance (Vinchur, Schippmann, Switzer III, & Roth, 1998) found age to be predictive of sales performance as rated by the supervisors but not predictive of OSP. When age was included in the regression equation of this study, i.e., in interaction with other variables, a relationship was found: age was the second highest impacting factor on TSP (24.6%), although it was found to be inversely related to the TSP. Rahim and Malik (2010) investigated the relationship between emotional intelligence and organizational performance in the banking sector in Pakistan. Measuring EI with the same scale used in this study, Rahim and Malik (2010) found that age has a negative relationship with emotional intelligence that affects organizational performance. The explanation of their finding was that youngsters are very energetic and inspired by good careers and professional growth, but they have been overextended; due to the long hours they must work to earn sufficient money for expenses, they have no time for social activities and families.
McDaniel, Pesta, and Banks (2012, p. 293) drew the conclusion that age has an inverted-U relationship with job performance where performance in most jobs starts to decline after age 50. They believed that this finding applies to people in less cognitively demanding jobs. However, those working in highly complex jobs, such as medical doctors and lawyers, where performance relies on an already-acquired knowledge structure, are expected to maintain their performance longer. In this research study, the average chronological age of the sales employees was approximately 37 years old. The OYES has the highest predictive value (41.6%) of TSP. Experience is associated with age. Chronological age is the most-studied conceptualization of age, although functional or biological age may also be relevant (McDaniel et al. (2012, p. 291). Functional age refers to the ability of the individual to perform the job based on mental and physical abilities. In this study, it was found that many of the sales employees had a “breadth” of sales experience, i.e., had worked in the sales profession but in different fields including automotive, IT, furniture, apparel, retail, make-up, telecommunication, and family business. The breadth of sales knowledge, professional practice, and acquired interpersonal skills through customer interactions apparently had increased their functional age while the sample studied was only 37 years old on average. This factor most likely positively influenced their TSP.
Limitations and ConclusionThere were some limitations in this study. First, because the study focused on the automotive industry in Kuwait, the findings are specific to this industry and cannot be generalized. Second, this research study is cross-sectional in nature; thus, it should be replicated in the automotive industry as well as other industries in order to gain more insight into the relationships between emotional intelligence and sales performance. Third, the researched population of salespersons was almost entirely expatriates due to the nature of this profession, Kuwaiti culture, and HRM practices. Thus, we were not able to investigate emotional intelligence among Kuwaitis. Perhaps another study can be designed to target Kuwaitis in different industries. Fourth, only one type of emotional intelligence scales—the self-report—was used in this study. The busy nature of the sales profession in general, and specifically within the Kuwaiti automotive industry, makes it very challenging to administer the time-consuming EI ability tests.
In conclusion, this research study is unique because it is the first to study the relationships between emotional intelligence and sales performance in the Kuwaiti market. The finding of a negative relationship between emotional intelligence and sales performance coupled with the positive relationship between total sales experience and sales performance encouraged the researchers to adopt the moderator model in future studies in order to accommodate the various moderators possibly contributing to this relationship. Moreover, the type of emotional intelligence scale is a critical issue, as reported in the literature and observed in this study. This factor urges EI researchers to consider a comparative study investigating the EI-performance relationships using ability test scales and self-report scales. Although many self-report scales have been designed and tested by Arabic researchers in their countries, there is a lack of a similar effort in terms of ability tests. Additionally, given the mixed findings in the emotional intelligence literature studying its relationship with performance throughout twenty years of investigation, the researchers of this study recommend conducting a longitudinal study that would help determine the nature of this relationship.
Conflict of InterestThe authors of this article declare no conflict of interest.
