The influence of Emotional Intelligence on Sales...

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“The influence of Emotional Intelligence on Sales Performance at Financial Service firms.”

A Research Proposal presented to:

The Graduate School of Business

University of Cape Town in partial fulfilment of the requirements for the

Master of Business Administration Degree

By: Jason Stanley

MOD274

Modular Program ‟09-„10

December 2010

Supervisor: Jean-Michel Jaquet

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TOP SALESPEOPLE HAVE HIGHER EMOTIONAL INTELLIGENCE SCORES

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PREFACE

Acknowledgements

There are people who assisted me completing this research report, which I would like to thank.

To the financial sales managers at Cape Province Financial Sales firms for agreeing to participate in

this research, in particular StanLib (Pty) Ltd for their participation and valuable advice – Thank-

you.

Thank-you Jean-Michael Jaquet for your calming supervision during this demanding time.

Thank-you Dino at the London Psychometric Laboratory in the United Kingdom, for helping me

obtain the correct Trait Emotional Intelligence Questionnaire and for addressing several of my

questions related to this study.

To my friends on the MBA program over the past two years, thank-you for all your support and

making it such a worthwhile experience I will never forget.

Lastly thank-you to my family for all your support over this entire MBA program. I am very

blessed to have you.

I certify that except as noted above the thesis is my own work and all references used are accurately

reported in footnotes.

Signed: Jason Stanley

Date: December 2010

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Abstract

Identification of the features that influence the performance of sales professionals is an undertaking

that has lasted for decades. The outcomes of such studies are especially valuable to financial sales

professionals. In the current study, higher emotional intelligence is hypothesized as being

positively related to sales person performance at Cape Province Financial Service Firms.

A Trait Emotional Intelligence Questionnaire (self-report measure) was sent to sales persons whose

managers had confidentially rated as either Top or Bottom sales performers. Quantitative and

demographic data was assembled, investigated, and statistical methods were used to test the

hypothesis.

Although the findings of this study indicate a weak link is observable, this study finds sales

performance is not statistically significantly related to emotional intelligence levels. Based on these

findings, suggestions for future research in the recently established field of emotional intelligence-

sales performance are presented.

KEYWORDS: Emotional Intelligence, Sales Performance, Trait Emotional Intelligence, Self-

report, Financial Sales Performance.

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Table of Contents

Preface ........................................................................................................................................................... 2

Acknowledgements ............................................................................................................................................... 2

Abstract ..................................................................................................................................................................... 3

List of tables ............................................................................................................................................................. 5

List of figures ........................................................................................................................................................... 5

Plagiarism declaration......................................................................................................................................... 6

1 INTRODUCTION .................................................................................................................................... 7

1.1 Research Area and Problem ................................................................................................................... 7

1.2 Research Questions and Scope .............................................................................................................. 9

1.3 Research Assumptions ............................................................................................................................10

1.4 Research Ethics ..........................................................................................................................................11

2 LITERATURE REVIEW ..................................................................................................................... 12

2.1 Emotional Intelligence and Sales Performance .............................................................................12

2.1.1 The Beginning – Social Intelligence .......................................................................................................... 12

2.1.2 Multiple Intelligences ..................................................................................................................................... 12

2.1.3 EI to mainstream .............................................................................................................................................. 13

2.2 Different Emotional Intelligence Models .........................................................................................15

2.2.1 The ability-based model ................................................................................................................................... 15

2.2.2 Mixed models of EI ........................................................................................................................................... 16

2.2.3 Trait EI model ..................................................................................................................................................... 16

2.3 EI Measures: Ability vs. Self-report ....................................................................................................17

2.4 Conclusion ...................................................................................................................................................19

3 RESEARCH METHODOLOGY .......................................................................................................... 20

3.1 Research Approach and Strategy ........................................................................................................20

3.2 Research Design, Data collection methods and Research instrument ..................................21

3.2.1 Research design ................................................................................................................................................ 21

3.2.2 Data Collection Methods ............................................................................................................................... 22

3.2.3 Research Instruments .................................................................................................................................... 22

3.3 Sampling .......................................................................................................................................................25

3.4 Research Validity and Reliability ........................................................................................................28

3.5 Data Analysis methods .............................................................................................................................29

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3.6 Characteristics of the sample ...............................................................................................................31

3.7 Research Analysis and Discussion .....................................................................................................34

3.8 Research Limitations ..............................................................................................................................36

4 RESEARCH CONCLUSIONS ........................................................................................................ 38

5 FUTURE RESEARCH DIRECTIONS ......................................................................................... 39

BIBLIOGRAPHY ........................................................................................................................................ 41

APPENDICES .............................................................................................................................................. 46

List of tables

TABLE 1 - DEMOGRAPHICS 31

TABLE 2 - EI RESULTS 32

TABLE 3 - AGE CHARACTERISTICS 32

TABLE 4 - EI RESULTS BY CATEGORY 33

TABLE 5 – COMPARATIVE TEIQUE STUDIES 34

List of figures

FIGURE 1 - EMOTIONAL INTELLIGENCE'S CONCEPTUALIZATION AND SCOPE 13

FIGURE 2 - SURVEY PARTICIPANTS 26

FIGURE 3 - SIX SECONDS ORG. STUDY OF EI AND AGE 27

FIGURE 4 - AGE-EI SCORE RELATIONSHIP IN THIS STUDY 27

FIGURE 5 - EI SCORES 33

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Plagiarism declaration

I know that plagiarism is wrong. Plagiarism is to use another‟s work and pretend that it is one‟s

own. I have used the APA convention to citation and referencing. Each contribution to, and

quotation in this report from the work(s) of other people has been attributed, cited and referenced.

This report is my own work. I have not allowed, and will not allow, anyone to copy my work with

the intention of passing it off as his or her own work.

Signed: _________________________________

Jason Stanley

December 2010

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1 INTRODUCTION

1.1 Research Area and Problem

Historically much is written on the features of top performing salespeople, who achieve superior

sales performance in relation to their peers. Variables determining sales performance have

interested marketing researchers for a long time (Churchill, Ford, Hartley, & Orville, 1985). The

purpose of this study is to measure the influence of Emotional Intelligence (EI) levels of

salespeople against their sales performance, within the Cape Province Financial Services (CPFS)

Industry in South Africa. This study seeks to gauge whether CPFS salespeople‟s EI scores impact

their sales performance. The financial services industry is driven to constantly innovate and make

most efficient use of resources. Consequently, this research may be of benefit to all CPFS firms

selling a product or service.

Previous research assessed variables relating to a salesperson‟s physical characteristics, such as

height, weight, attractiveness, and age; personality characteristics, including gregariousness,

extroversion/introversion, self/other orientation; and various other characteristics, such as

intelligence, similarity to buyers, education, and so on. However, the results of previous research

have often been inconclusive (Ford, Orville, Gilbert, & Hartley, 1988). A limit on previous

research is based on the fact that many of the variables are not easy to implement (e.g., similarity to

buyer), measure (e.g., personality characteristics) or are not changeable (e.g. cognitive intelligence)

(Rozell, Pettijohn, & Parker, 2006). Nevertheless the pursuit continues for variables that infuluence

sales performance, which are implementable, measurable and changeable.

This research is motivated by the observed evidence of individual different variables of EI

(Goleman 1995, 1998; Mayer & Salovey 1993, 1995). It is theorized EI affects several workplace

circumstances including sales performance, job satisfaction, absenteeism, organizational

commitment, and leadership (Cooper & Sawaf 1997; Gates 1995; Goleman 1995; Megerian &

Sosik 1996, 1999; Wright, Bonett, & Sweeney 1993). The fact that EI is measurable is important

for sales performance research. Additionally, and perhaps of more significance is the fact that by

measuring EI, salespeople may discover their EI score is not adequate to attain optimal sales

performance. In such a situation, salespeople may through training increase EI levels. According to

Goleman (1995; 1998), unlike Gates (2000) EI is changeable.

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Rozell et al (2006) conducted a study finding that emotional intelligence is significantly related to

sales performance. Further specifically EI-Sales Performance research is notably absent in

academic literature.

If this study confirms EI is positively related to sales performance, there is also the possibility this

research could have a broader beneficial application for various sectors outside of CPFS where

sales take place.

This research measures the EI of two separate groups within the CPFS Industry. The two groups

are: 1. „Top 20% Performing Salesperson‟ (within their respective sales team) and 2. „Bottom 20%

Performing Salesperson‟ (within their respective sales team). These two groups were selected from

a number of CPFS firms, agreeing to participate in this research. Each surveyed participants EI

score is measured. Survey participant‟s data is then collated within their relevant group. The two

groups EI data is then compared, and tested for correlation to sales performance.

The significance of this research lies firstly in terms of its contribution to the body of knowledge, as

it provides an extension to research conducted by Rozell and others (Rozell et al, 2006). Rozell et

al‟s study found EI positively related to sales force performance of a USA firm engaged in the sale

of medical devices. Their study applied several self-report scales to measure sales performance

and EI. For research purposes, this study will add to the lack of EI testing in the financial service

sector. It also serves as a yardstick for future research to consider the use of a self-report

questionnaire, in particular the Trait Emotional Intelligence Questionnaire (TEIQue-SF).

Moreover, the results of the research could be meaningful outside of academia to business

managers and especially sales managers, who may benefit from further knowledge to increase their

sales. The research will be of importance to business people linked to sales, if it can provide further

knowledge of factors that may increase sales rates at financial service firms. This would

consequently improve financial service firms‟ levels of service and profits. The significance is in

the knowledge that sales peoples increased ability may better future sales performance. The

importance in understanding the impact of this research is based on two perspectives.

(1) Assessing new salesman recruits: With added foresight that new hires with higher EI

levels are likely better salespeople, managers can make more informed hiring decisions. This could

lead to the selection of more successful sales teams.

(2) Assessing of existing salespeople: Sales managers can evaluate the EI of existing

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salespeople; and where necessary apply strategies to increase EI levels. This could potentially

increase sales performance and profitability.

1.2 Research Questions and Scope

The intention of the research is to understand the influence of EI on sales person performance at

CPFS firms. The main hypothesis under investigation is therefore stated as:

Hypothesis 1:

H0: There is no difference between the mean EI scores of Top and Bottom performing

salespeople at CPFS firms.

H1: There is a difference between the mean EI scores of Top and Bottom performing salespeople

at CPFS firms.

Sales persons from various Cape Province Financial Services firms were investigated. The scope of

the research was limited to eight separate sales teams across three separate SAFS firms. The

financial sales people surveyed sell financial products to end consumers or to other financial

brokers. No sales managers were surveyed for EI.

In terms of scope, this study elected to focus exclusively on the two separate groups. Firstly „Top‟

performers, who are amongst the „Top 20% Performing Salespersons‟ (within their respective sales

team). Secondly, „Bottom‟ performers who are amongst the „Bottom 20% Performing

Salespersons‟ (within their respective sales team). Sales people „in the middle‟ were not surveyed,

or their data was omitted if they did erroneously respond.

The sample of salespersons surveyed market a wide range of financial products, including asset

management, wealth management, unit trust interests, debt management plans and formal debt

review processes for both institutional investments and individual investments.

This study aimed to identify if there is a causal relationship between salespeople with higher EI

scores and higher sales performance at CPFS firms. Future studies will be able to expand on,

support or deny the claims made in this study.

The importance of this study from a business management perspective is that it may reveal findings

that influence how sales force recruitment and sales training policies are reviewed and enhanced in

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future.

The time frame of approximately 10 weeks was used for the research, and this may have limited the

opportunity of reaching a wider participation on survey of CPFS salespersons.

1.3 Research Assumptions

Some of the main assumptions fundamental to this research are the epistemological and ontological

assumptions, regarding the nature of this research.

From an epistemological perspective, a positivist epistemological position is taken with the

research in this study. Empirical and statistical analyses of data representing social reality (Sales

Performance and EI scores), using robustly reviewed academic models were used during this study

to determine outcomes (t-test & Levene‟s test).

Positivist research should apply research methods advocating facts being collected, rather than

personal values of study participants e.g. the researcher (Bryman & Bell, 2007). This research

adopted a quantitative approach, using a statistical model (i.e. TEIQue-SF EI self-test) that is

independent of the researcher‟s influence.

The other assumptions for this research relate to the main question. Firstly, the Cape Province

Financial Services industry is broad and it might not be easy to identify sales managers/sales people

interested in investing time in an EI survey. There are also issues around confidentiality of sharing

employee information with people outside their firm. This proposal is based on the assumption

there is a sufficient number of sales managers and salespeople at CPFS firms willing to participate

in this research.

It is also assumed that sales managers will provide accurate lists of their Top & Bottom sales

performers. „Top sales performers‟ will be considered to be in their respective firm/sales team‟s

Top 20% of sales performers. „Low sales performers‟ are considered to be in the respective firms‟

bottom 20% of sales performers. Sales Performance in this study is reliant on the advice from

respective sales managers. It was agreed by all sales managers that their assessment of Top and

Bottom performing salesperson is based closely on net profit generated for the firm, which is

usually related to income generated by the salesperson.

There may be firms unidentified by the researcher interested in EI measurement. However, this will

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not be a critical factor in the research because a deliberate sampling will be done. A representative

selection will be done to cover for a representation of the SAFS industry view.

1.4 Research Ethics

No ethical problems were encountered in this research.

Permission was obtained from the various sales managers of all CPFS firms and sales teams

requested to participate in this study. All sales people and sales managers participating in this study

remained anonymous. A guarantee of anonymity was assured to survey participants. All

respondents were over 18 years of age and were company employees at reputable CPFS firms.

All survey data was stored in Excel spreadsheets on secure drives.

An ethical clearance form was submitted online and approved by the University of Cape Town

(UCT) Ethics Committee.

The EI model and survey used was the TEIQue-SF EI self-test, designed to measure a person‟s

Global Trait EI. Permission to use this test for academic purposes appears on London Psychometric

Laboratory‟s (LPL) website - www.psychometriclab.com. Permission to use the test was also

confirmed via email with LPL.

Ethical considerations for this research include linking names to data obtained that could

compromise the images of the survey participants involved. This was addressed by only working

with data that will not be linked to the surveyed individuals if it has a potential to jeopardize them

or their company. Data will be presented in codes that cannot be linked to the subjects surveyed.

Also, the personal details collected will be treated as confidential, and no response will be linked to

individuals.

http://www.psychometriclab.com/

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2 LITERATURE REVIEW

2.1 Emotional Intelligence and Sales Performance

2.1.1 The Beginning – Social Intelligence

Thorndike (1920) a psychologist from Columbia University was the first to propose the concept of

Social Intelligence. Thorndike said, “Social Intelligence shows itself abundantly in the nursery, on

the playground, in barracks and factories and salesrooms, but it eludes the formal standardized

conditions of a testing laboratory” (Thorndike, 1920). Thorndike proposed that additional abilities

exist and need to be viewed separately from general intelligence. Thorndike‟s main suggestion was

that the understanding and perception of our personal feelings, as well as those of others, is a

separate type of intelligence from one‟s general intelligence (Thorndike, 1920).

By the late 1950‟s Wechsler a dominant psychologist in his day who created what still remains one

of the most widely used measures of IQ, dismissed social intelligence. Wechsler viewed Social

Intelligence as, general intelligence applied to social situations (Wechsler, 1958).

2.1.2 Multiple Intelligences

Gardner (1983), expanding on Thorndike‟s concepts developed a theory of multiple intelligences.

Gardner suggested a more complex set of capabilities would allow for better measurement and

development of other kinds of intelligence. Gardner‟s main point in his theory of multiple

intelligences tried to provide an understanding that intellectual activities can exist independently of

each other.

Salovey and Mayer (1990) suggested a more focused division of intelligences. Defined as the skill

to understand emotions and feelings in oneself and others and to use this understanding as a way to

solve problems and regulate behavior; the phrase „emotional intelligence‟ was born.

Following this explanation, the theory of EI is suggested to involve three abilities. Firstly, appraisal

and expression of emotion; secondly, regulation of emotion; and lastly, utilization of emotion as

intelligence. See Fig 1 below.

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Figure 1 - Emotional Intelligence's Conceptualization and Scope

Source: (Salovey & Mayer, 1990)

Expression of emotion includes the ability to express personal emotions verbally and nonverbally,

and also to perceive and understand the emotions of other people. Regulation of emotion includes

the ability to be skillful at using emotion to influence moods in one‟s self and others. Lastly,

utilizing emotional intelligence, suggests an emotionally intelligent person is able to use their

emotions to successfully choose more effective solutions to their problems (Salovey & Mayer,

1990). This theory provided an important basis for future research about emotional intelligence.

2.1.3 EI to mainstream

Goleman (1995; 1998) is credited to have brought the theory of emotional intelligence into

mainstream thinking. As a model, Goldman suggested emotional intelligence encompassed five

parts: self-awareness, self-regulation, self-motivation, empathy, and social skills. Each of the five

competencies is proposed to have an impact on the way a person observes and responds to all life

experiences. Goleman‟s (1995; 1998) views seem to relate closely to the behavior and traits of a

successful salesperson.

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To do well, the salesperson needs to have control of and self-awareness of their feelings. Rozell et

al., (2006) suggest in the field of personal selling, salespeople face denial, rejection, role conflict,

and role ambiguity; and frequently take on these challenges without the support common in other

forms of employment. When salespeople are faced with disrespect and negative responses they

need to be able to separate themselves from negative results. Correspondingly, when salespeople

are faced with positive results they need to be aware of their part in producing those results. Thus it

appears better self-regulated salespeople have advantages over there lesser well self-regulated sales

peers (Rozell et al., 2006).

Self-regulation is linked closely to behavior, because it encompasses self-control, adaptability, and

self-monitoring within a situational context. Additionally, behaviors such as empathy and

motivation are argued to influence the way people recognize events and indirectly influence their

reactions (Goleman D. , 1995).

Self-motivation is another important factor in successful salespeople. Ford et al. (1988) suggested

that when it comes to optimal salesperson selection; the best natural features a new recruit should

possess are related to EI and motivation. Sojka & Deeter-Schmelz (2002) suggested a component

of EI is self-motivation, and they expected a positive relationship between EI and motivation.

Salespeople are often „in the field‟, and as a result directly unsupervised. As a result of this lack of

direct supervision, self-motivation is often an important factor in determining successful sales

performance. In many aspects of a salespersons role such as cold calling, dealing with busy

customers, price negotiations etc., self-motivation is often important.

Another feature often thought to be important for successful sales is empathy. Spiro & Weitz

define empathy as "the reaction of individuals to the observed experiences of other individuals"

(1990, p. 63) and argue that empathic capacity is directly related to sales ability. Their reasoning is

that these skills allow the seller to incorporate useful information during sales presentations to

improve sales techniques with potential buyers with mixed needs. Thus, the better a sales person

can empathise with their customers, the more likely their sales performance is likely to benefit

because of better-tailored solutions towards customers empathetic needs (Spiro & Barton, 1990).

Lastly, the sales environment frequently involves a great deal of social interactions.

Conferences/Business drinks etc. are often an important part of the sales job function. Thus,

Goleman‟s (2005) last factor of emotional intelligence, social skills, would appear to be closely

connected to sales performance.

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Since these above listed characteristics making up EI are said to influence sales performance, it is

reasonable to believe that a higher EI score is a factor that will result in improved sales

performance.

2.2 Different Emotional Intelligence Models

Various different models have been put forward as the definition of EI, and there is a difference of

opinion as to what the most appropriate classification is. (Mayer, Salovey, & Caruso, 2008)

There are three main models of EI:

Ability EI models

Mixed models of EI

Trait EI model

There is disagreement amongst the various models on two main points. Firstly, regarding the

terminology (i.e. study of terms) and secondly regarding operationalizations (i.e. process of

specifying the extension of a concept) referred to in each model. Because the EI field is growing so

rapidly, regular re-evaluation of researchers‟ definitions is common.

2.2.1 The ability-based model

Salovey et al‟s (2008) most recent definition of this EI model involves the ability to perceive

emotion, integrate emotion to facilitate thought, understand emotions and to regulate emotions to

promote personal growth.

Salovey & Grewal (2005) suggested the ability model sees emotions as valuable sources of

information that assist people to make sense of and navigate their social interactions.

This model suggests people differ in their ability to process information of an emotional nature, and

in their ability to utilize that emotional information. This ability is seen to make itself apparent in

four types of ability:

1. Perceiving emotions (of others and in oneself)

2. Using emotions (to channel emotions to facilitate cognitive needs)

3. Understanding emotions (recognising relationships among emotions)

http://en.wikipedia.org/wiki/Extension_%28semantics%29

http://en.wikipedia.org/wiki/Concept

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4. Managing emotions (in ourselves and others)

Bradberry & Su (2003) argued the ability model lacks face and predictive validity in the workplace.

2.2.2 Mixed models of EI

As discussed above in this literature review, Goleman (1998) suggested EI centres on a wide range

of capabilities and skills that enhance people‟s performance. Goleman's model (1998) puts forward

five main EI traits.

1. Self-awareness (ability to read one's emotions and use „gut‟ to make effective decisions)

2. Self-management/regulation (ability to control one's emotions and adjust to changing

conditions)

3. Self-motivation (ability to improve one‟s emotions)

4. Social awareness/Empathy (ability to sense, understand, and react to others' emotions)

5. Relationship management (ability to motivate, persuade, and advance others while

managing disagreement)

Inside each trait of EI, Goleman (1998) suggests a group of emotional competencies. These

competencies are not natural talents, but to a certain extent learned abilities that can be improved if

trained and developed. Goleman also suggests that people are born with a general emotional

intelligence that to a large extent establishes their capability for learning emotional competencies

(Boyatzis, Goleman, & Rhee, 2000).

Mayor, Roberts & Barsade (2008) critique Goleman's model of EI‟s mixed-in traits lack a primary

focus on EI. Mayor et al. suggest variables included in mixed models such as assertiveness and

need for achievement are important to study as part of EI.

2.2.3 Trait EI model

Petrides et al. (2007) suggested a difference between the ability based model and a trait model of

EI. Petrides & Furnham (2000) suggested Trait EI to be a collection of emotional self-perceptions

located at the lower levels of personality. This definition of EI includes behavioral characteristics

and self-perceived abilities. Petrides & Furnham (2001) suggest Trait EI should be examined

within a personality framework. An alternative label for Trait EI is trait emotional self-efficacy.

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The trait EI model builds on the Goleman‟s mixed model discussed above. Petrides & Furnham

(2000) go on to suggest the conceptualization of EI as a personality trait leads to a construct that

lies outside the structure of human cognitive ability. This is an important distinction in that it bears

directly on the operationalization of the construct and the theories and hypotheses that are

formulated about it (Petrides & Furnham, 2000).

2.3 EI Measures: Ability vs. Self-report

Deciding what type of test to use to measure EI is a contentious issue.

In MacCann, Matthews, Zeidner, & Roberts, (2003) psychological assessment of EI, reviewing

Self-Assessment and Performance based testing, it was found self-report techniques measure a

dispositional construct, that may have some predictive correlation, but which is highly correlated

with personality and independent of intelligence. Performance based measures were also found to

have restrictions especially when scored based on consensual norms which leads to problems of

skew and restriction of range. Other difficulties with performance measures include limited

predictive and operational validity, restricting practical utility in organizational settings (MacCann,

Matthews, Zeidner, & Roberts, 2003).

Davey (2005) suggested that initial theory did not recognize the importance of the differentiation

between the underlying notions of self-report and ability measures. This has caused some

uncertainty and disagreement regarding the findings of numerous previous studies (Davey, 2005).

Perhaps the reason for past indecision on previous studies is because EI has been defined in various

ways in existing literature. Mayer and Salovey (1997) explain EI as the „ability to perceive

accurately, appraise, and express emotion; the ability to access and/or generate feelings when they

facilitate thought; the ability to understand emotion and emotional knowledge; and the ability to

regulate emotions to promote emotional and intellectual growth‟ (Mayer & Salovey, 1997, p. 10).

Other studies adopted a wider view of EI, in doing so extended the cognitive ability model of

Mayer and Salovey (1997). These new studies contain additional factors such as zeal, persistence,

or assertiveness (Bar-On, 1997; Goleman, 1995), and therefore include personality traits as well as

mental abilities.

Davey (2005) suggested the measurement of EI by ability test, will not always yield the same result

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as EI measured with a self-report test – based on the same sample. It is important to understand that

the different models of EI represent different constructs, differentiated by their measurement

methods used to operationalize them, rather than by the content of the sampling. This implies that

in the event of the different measures used on the same sample, one can expect to possibly obtain

different results for the same sample group (Davey, 2005).

Petrides and Furnham (2001) further proposed the classification of trait and ability EI. According to

Petrides, Pita, & Kokkinaki (2007) trait EI can include emotion-related dispositions and self-

perceptions. Trait EI is based on self-report measures and evaluates typical styles of behavior,

whereas ability test uses ability measures (e.g. the Mayer–Salovey–Caruso Emotional Intelligence

Test, MSCEIT), and refers to maximum performance in processing emotional information (Mayer

and Salovey, 1997).

Trait and ability EI methods have both received critical reviews. However, representatives of both

the trait and ability EI approaches agree that significant improvement of both concepts has been

achieved in recent years (Petrides et al., 2007). To date, there has been no published study

providing a comprehensive analysis of the validity of an EI measure that is ideal when measuring

sales people‟s performance (Petrides & Furnham, 2001).

Further criticism of consensus-based assessment methods are offered by Roberts, Gates &

Matthews (2001). They argue ability-based tests measure conformity, not ability. One criticism of

the works of Mayer and Salovey, which suggests that EI measured by the MSCEIT, may only be

measuring conformity. This argument is rooted in the MSCEIT's use of consensus-based

assessment, and in the fact that scores on the MSCEIT are negatively distributed; meaning its

scores differentiates between people with low EI better than people with high EI.

Ability based measures are measuring knowledge (not actual ability). Further criticism has been

offered by Brody (2004), who claimed that unlike tests of cognitive ability, the MSCEIT tests

knowledge of emotions, but not necessarily the ability to perform tasks that are related to the

knowledge that is assessed. Brody‟s main argument is that even though someone knows how he

should behave in an emotionally loaded position, it doesn‟t necessarily follow that they could

actually carry out the reported behavior.

One major criticism of self-report assessments is sometimes informally referred to as „faking good

results‟, or more formally termed „socially desirable responding‟. In these cases test-takers

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characterize themselves with an excessive positive bias (Paulhus & Delroy, 1991). This favoritism

has long been known to contaminate some responses on personality inventories (Holden, 2007).

The main concern for this study with the ability EI test relates to ease of access of the test, the cost

of the test, and possible issues that may occur when scoring the test. Measurement of the test is an

issue, due to the subjective nature of emotional experiences that weaken the ability to create test

questions along cognitive ability lines (Davey, 2005). The scoring procedure raises concern because

it has not proven to be successful in operationalizing cognate theories, like social intelligence

(Davey, 2005). For reasons mentioned above, a self-report measure has been chosen for this study.

2.4 Conclusion

Much is written about the features of top performing salespeople, and the variables determining

sales performance. This research aims to measure the impact of EI on salespeople within the CPFS

industry, and gauge whether EI levels impacts their sales performance. By doing so, this study will

add to the limited academic understanding of the concept of EI‟s impact on sales performance.

The above literature review puts forward a strong case for why EI may positively impact a

salespersons performance. This research may be of benefit to all CPFS firms selling products or

services in what is an increasingly competitive business world. There is the possibility this research

could have broader beneficial application for various other business sectors.

For research purposes, this study will add to the lack of testing of EI in the CPFS sector and serve

as a yardstick for future research to consider the use of a self-report questionnaire, in particular the

Trait Emotional Intelligence Questionnaire (TEIQue-SF), in the CPFS firms.

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3 RESEARCH METHODOLOGY

3.1 Research Approach and Strategy

A deductive approach is the main research method in this study. In deductive research, the

researcher takes what is accepted about a specific idea and of the theoretical considerations related

to that idea and deduces a hypothesis (Bryman & Bell, 2007). This research is conducted with

reference to hypotheses and ideas inferred from existing theory that is relatively new and somewhat

untested in this studies context. This research used various categories (e.g. Top Performer or

Bottom Performer) and measures such as mean and standard deviation to arrive at, and either prove

or disprove the hypothesis (Bryman & Bell, 2007).

The intent of this research is to contribute towards establishing, confirming, or validating

relationships and to develop generalizations that contribute to theory (Leedy & Ormond, 2010).

A quantitative approach is the measurement method used, as a questionnaire is utilized to collect

statistical data. (Bryman & Bell, 2007)

In terms of epistemological & ontological orientations, this study advocates the relevance of the

methods of natural sciences to examining social reality and beyond. At the same time, elements of a

deductive approach and an inductive strategy are utilized. For these reasons, a positivism strategy

is adopted for this study under epistemological orientation.

This study presumes that social phenomena and categories are not only produced through social

interaction and they are in a constant state of revision. Therefore, this study assumes a

constructivism position (Bryman & Bell, 2007).

This study considers the following hypothesis:

H0: There is no difference between the mean EI scores of Top and Bottom performing

salespeople at CPFS firms.

H1: There is a difference between the mean EI scores of Top and Bottom performing salespeople

at CPFS firms.

The main assumptions of this research are as follows:

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There is a correlation between EI and salespeople performance (Rozell, Pettijohn, & Parker,

2006)

The identified Top sales performers will score higher EI scores than identified Bottom sales

performers. (Rozell et al., 2006)

The Top and Bottom sales groups provided by sales managers for this study will accurately

reflect Top & Bottom sales performers.

An inductive approach is adopted for the study of this main hypothesis. There is currently no

research on EI & Sales performance in the CPFS sector that this writer could locate. The opinion

for this inductive study is based on the deductive theory and limited research that exists related to

the link between EI and the performance of salespeople. The literature linking the emotional

intelligence to sales performance is severely lacking. Rozell et al‟s (2006) study is one of the first

on EI & sales performance studies suggeted replications should be performed to clarify whether the

scales used in their study are valid and dependable measures of EI (Rozell et al., 2006). Thus, this

study would assist to validate Rozell et al‟s (2006) study, and build on the dependability of their

measures.

There is also reason to believe that higher emotionally intelligent salespeople will be more

successful at their jobs if they possess higher abilities in the personal and social dimensions of EI

(Meyer & Zizzi, 2007). Therefore, the hypothesis is drawn on the above-mentioned literature and

the assumption that higher EI scorers will in general be better sales performers.

3.2 Research Design, Data collection methods and Research

instrument

3.2.1 Research design

After the literature review and establishment of this study‟s hypothesis, various researchable CPFS

firms‟ sales managers were approached to participate in this study. Willing respondents were

engaged with via email/telephone/in-person. This was followed by a request for a list of Top

Performing sales staff and Bottom Performing sales staff. Next, sales staff were communicated

with via email, and the collection of data through self-completion surveys took place. Next, the

researcher performed quantitative analysis on the data. Lastly, certain conclusions were arrived at.

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Sampling of survey participants was non-probable, and chosen from all race groups. Survey

participants are from two distinct groups, namely the „Top‟ salespeople (defined as the top

performing 20% of their respective sales team) and the „Bottom‟ salespeople (defined as the bottom

performing 20% of their sales team). Sales Managers from various CPFS firms were requested to

confidentially provide names and contact details for salespeople in these two groups. The

identified Top and Bottom salespeople were then contacted, without it being made known to them

whether they were part of a Top or Bottom sales performance group and requested to complete a

TEIQue-SF EI survey. The TEIQue-SF surveys purpose was to score salespeople‟s EIs.

All salespeople were from reputable CPFS firms. A reputable firm in this study entails being listed

on the JSE, with a 10-year track record. One exception was made in the case of Debt Busters (Pty)

Ltd that is a privately held SAFS firm headquartered in Cape Town.

All salespeople surveyed were required to have a minimum of five years‟ experience selling

financial products, in order to participate in this study. There was no maximum amount of financial

services sales experience excluding a potential sample. Samples were selected from salespeople

selling a range of financial products.

3.2.2 Data Collection Methods

CPFS sales managers confidentially identified Top and Bottom performing salespeople. These

sales people were then e-mailed and requested to complete and return e-mail a TEIQue-SF EI

survey and certain demographic details. (See Appendix1).

This study required:

Contact information of relevant salespeople at the various SAFS companies involved.

Salespeople broken into „Top 20%‟ & „Bottom 20%‟ sales performance groups.

All surveyed salespeople‟s EI scores.

Surveyed salespeople‟s personal details including Name, Age, Gender and Ethnicity.

3.2.3 Research Instruments

It is important to note that amongst a large variety of EI test options; this study uses the TEIQue-SF

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test to measure the EI of all surveyed salespeople (See Appendix 1). Reasons why this test is used

in this study are detailed above in section 2.3 of this paper. These tests are available free of charge

for research purposes and can be downloaded from the London Psychometric Laboratory (LPL)

website - www.psychometriclab.com.

It was decided to use the TEIQue-SF test comprising 30 questions, designed to measure a global

trait EI score. Test completion time was approximately 7 minutes (www.psychometriclab.com,

2010).

26 of 30 identified participants completed the TEIQue-SF test for trait emotional intelligence. The

full test consists of 30 items that is rated on a 7-point Likert scale ranging from 1 (Strongly

Disagree) to 7 (Strongly Agree). Higher scores on the TEIQue-SF indicate higher levels of trait

global emotional intelligence (www.psychometriclab.com, 2010).

There are a number of different TEIQue tests available. After explaining the nature of this study

and consultations with the test administrators at London Psychometric Laboratory, the researcher

decided a TEIQue-SF test was the most appropriate for this study. The selection of this test was

influenced by initial feedback from various sales managers at CPFS firms. Sales managers

indicated a higher response rate would be obtained for the shorter 7-minute test, than the longer

TEIQue v. 1.50 of 153-question test, which takes approximately 30 minutes to complete.

The writer and the staff at London Psychometric Laboratory felt a higher response rate due to a

shorter test being utilized would benefit this study, because a shorter test promoted a higher

response rate amongst requested survey participants. This is assumed to have reduced this studies

sampling errors. This is evidenced by the fact that of the 30 participants willing sales managers

identified as Top 20% or Bottom 20% sales performers, 26 of these 30 completed surveys. This

represents a high response rate of 86.66%. This writer and the staff at London Psychometric

Laboratory assume the benefits of this high response rate, and resultant reduction in sampling errors

outweighed any systematic errors due to a shorter test being used.

The theory of trait emotional intelligence (trait emotional self-efficacy) appears after the distinction

between two EI constructs names „ability EI‟ and „trait EI‟ (Petrid& Furnham, 2000). Petrides &

Furnham (2000) proposed a conceptual distinction between the two types of EI, based on the

assessment method used to measure them.

Trait EI concerns a group of emotion related and self-perceptions and dispositions. This construct




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pertains mainly to the construct of personality, and should thus be measured via self-assessment.

Ability EI concerns the actual ability to perceive, process and utilize affect-laden information. This

construct pertains mainly to cognitive ability, and should be measured via performance tests.

(Osofsky, 1991)

The trait emotional intelligence (trait EI) model successfully integrates and extends EI related ideas

in a general framework that incorporates 15 specific facets.

Adaptability Assertiveness

Emotion appraisal (self and others)

Emotion control

Emotion expression

Emotion management (others)

Low impulsiveness Relationships

Self-esteem

Self-motivation Social awareness

Stress management

Trait empathy Trait happiness

Trait optimism

The TEIQue v1.50 test assesses all of the above facets through 15 subscales. In addition, it provides

scores on four factors of broader relevance („well-being,‟ „self-control,‟ „emotionality,‟ and

„sociability‟). Information about each of the scales and factors is available at

www.psychometriclab.com. It is important to remember that scores on the trait EI facets do not

reflect cognitive abilities (e.g., IQ), but rather self-perceived abilities and behavioral dispositions

(Laboratory, 2010)

The psychometric development of this instrument is described in Petrides (2001), and a full

technical manual is currently in distribution.

In terms of sample demographics data collection, the TEIQue test contains a section at the end to

collect data regarding demographics of survey participants. This section includes information such

as gender, date of birth, marital status, income bracket, religion, and race. All of this information is

standard procedure for the London Psychometric Laboratory to obtain demographic data about their

samples.

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In this study, only certain demographic data was requested. Reduced demographic data was

requested, as sales managers initial advice was that the survey would have a higher and more

accurate response rate if certain additional questions were omitted (e.g. Annual Income Level,

What Religion are you? How religious are you?). Asking these additional demographic questions

would reduce the response rate in the sales managers in this writer‟s opinion, and thus possibly

increase the probability of sampling errors. Please refer to Appendix 1 for a sample of this studies

demographic questionnaire. For a full copy of the TEIQue v1.50 test and demographic questions

please see Appendix 3.

3.3 Sampling

Firstly, various CPFS sales managers were approached via in-person meeting/telephone

communication/email and requested to participate in this study. Sales managers agreeing to

participate were asked for contact details of „Top 20%‟ and „Bottom 20%‟ sales performers within

their particular CPFS firm/team. Most sales teams identified were groups of 10-20 in sales people

size. Thus, generally only the Top 2 and Bottom 2 salespeople within each team were sampled.

The „Middle‟ sales performers within the various teams were not requested to participate in this

survey.

Many CPFS firms approached declined to be involved for a number of reasons. By far the most

frequent reason for non-participation related to confidentiality policy issues within certain

organizations. These organizations had policies mandating that staff information not be disclosed

to anyone outside of their firm. The second most frequent reason for non-participation was time

constraint pressures. These firms could not justify the time to be spent compiling Top and Bottom

performers sales performers lists, and having their sale staff fill out questionnaires being worth the

potential upside of added insight on EI and sales performance.

In total, 8 different sales teams across these 3 CPFS firms agreed to participate in this study. The

size of each of these teams was an average of 12 sales people. The smallest sales team was 6 sales

people (StanLib Kimberly) and the largest team was Debt Busters (30 sales people). With the

exception of the Kimberly sales people from StanLib, all other the sales teams surveyed were based

in the Western Cape.

Firms that participated in this study were:

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StanLib (Pty) Ltd – 6 separate regional teams participated in this study. These were Cape

Town, Cape Peninsula, New Century, Two Oceans, Paarl and Kimberly. Established in 2002

through the merger of Liberty and Standard Bank's asset management, wealth management and unit

trust interests, with R330 billion assets under management, StanLib is a leading South African Unit

Trust Company (www.stanlib.com, 2010).

Prudential Portfolio Management (Pty) Ltd - The Cape Town regional team partook in this

study. In 1994 and 1996 Prudential established investment management offices in Cape Town,

South Africa and Windhoek, Namibia respectively. The assets that Prudential manage includes

institutional investments and individual investments from South African clients as well as

investment into the region from global investors (www.prudentail.co.za, 2010).

Debt Busters (Pty) Ltd – Cape Town regional team partook in this study. Debt Busters offer

debt management plans and formal debt review processes (www.debtbusters.co.za, 2010).

Figure 2 - Survey Participants

Secondly, after „Top‟ and „Bottom‟ sales groups contact information were obtained, the TEIQue-SF

EI self-assessment questionnaire compiled by London Psychometric Laboratory was emailed to all

relevant salespeople samples.

Mayer, Salovey & Caruso (2000) suggested EI increases with age. The study found there to be a

relationship between age and EI, but only slight. See Fig 2 below.

All participants selected were between the ages of 25-65 years old. In another study by Six Seconds

Inc., an Emotional Intelligence organization in the USA sampling 405 American people between 22

StanLib n=17

Debt Busters n=4

Prudentail n=4

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and 70 years old were studied.

Figure 3 - Six Seconds Org. study of EI and Age

Source: Six Seconds Inc.

Figure 4 - Age-EI score Relationship in this study

As can be seen from Fig 4 above, the EI-Age trend line in this study is slightly negative in this

study, compared to the Six Seconds Inc. study that is slightly positive. This is not deemed

significant to the outcomes of this study, because in both cases the trend lines are weak.

0

50

100

150

200

250

Age

EI Score

Linear (EI Score)

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3.4 Research Validity and Reliability

Validity of data refers to the question of whether or not formulated indicator to gauge a theory

really measures that concept. Reliability of data refers to the consistency of measure of a theory,

and involves three prominent factors. These three factors are stability, internal reliability and inter-

observer consistency (Bryman & Bell, 2007).

A potential validity concern with this study is the Self-report vs. Performance based measurement

issue. The limitation of self-report tests is discussed in this studies literature review above (See

2.3). Furthermore, Mayer, Salovey & Caruso (2004) suggest self-report tests are a poor EI measure

due to their objective bias, and that results indicate a “perceived” EI. The real EI self-report

measures tend to connect closely to personality rather than EI (Lane, et al., 2009). Wells &

Sweeney (1986) conducted a study testing bias in Self-Assessment testing. Their findings showed

that people with lower self-esteem, in contrast to those with higher self-esteem tend to overrate

their ability according to standardized norms in order to increase self-esteem (Wells & Sweeney,

1986).

Given a self-assessed EI test measure is used, another concern could be the validity and reliability

of the particular TEIQue test chosen in measuring EI. Several articles are written substantiating the

validity of the TEIQue EI tests validity. An example of such support for TEIQue comes from

Memar et al‟s (2005) study to determine validity and reliability of TEIQue‟s Trait Emotional

Intelligence questionnaire (Petrides & Furnham, 2001). The findings of this 2005 study were high

correlations among different scales confirming the convergent validity of the scales. The internal

consistency and test-retest methods indicated scale reliability at 0.76 and 0.71. More support

comes from Gardner & Qualter (2010) concluding for researchers interested in using trait EI, their

study suggests the TEIQue is a superior measure over MEIA and SEIS (both based on the Salovey

& Mayer [1990] model). See Appendix 4 – Adjusted square correlation coefficients table for

predicting EI (Gardner & Qualter, 2010).

Given that a TEIQue test is used, another validity concern could be the fact the shorter version

TEIQue-SF version containing 30 questions survey is used, as opposed to the full version TEIQue v

1.50 containing 153 questions. This concern is refuted by Cooper & Petrides (2010) who examine

the psychometric properties of the Trait Emotional Intelligence Questionnaire–Short Form

(TEIQue–SF; Petrides, 2009) using item response theory. Cooper & Petrides (2010) concluded, the

findings of the two studies suggest clearly that the TEIQue–SF can be recommended for the rapid

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assessment of individual differences in trait EI (Cooper & Petrides, 2010).

The TEIQUE-SF test incorporates a part reverse scoring method primarily to reduce response rate

bias (Idaszak & Drasgow, 1987). See Appendix 2 for a copy of TEIQue-SF reverse scoring sheet,

compiled by LPL. In recent years, however, reverse scoring use has come under close scrutiny by a

number of researchers. Reverse scoring of items has been shown to reduce the validity of

questionnaire responses (Schriesheim & Hill, 1981) and may introduce systematic error to a scale

(Jackson, Wall, Martin, & Davids, 1993).

The reliability of the TEIQue measuring tool, in light of Cross Cultural issues is something that

should be considered. The TEIQue was developed in the United Kingdom. Investigation is needed

to confirm this tool is dependable to use in a South African context, or whether there are cross-

cultural issues that would deem such a test undependable in South Africa (Bailie & Ekermans,

2006). Mayor et al (2004) backed up this concern stating there is a good correlation between culture

and EI.

3.5 Data Analysis methods

Data analysis was out carried in 4-step process:

1. A database was set up in Microsoft Excel capturing all respondents’ data of TEIQue-SF EI

scores and demographic data. (See Appendix 6)

2. Irrelevant responses (i.e. 4 Middle performers responded) and outliers (i.e. 1 was found) were

removed from the dataset.

3. Sample EI scores and demographic data were analyzed in the form of descriptive statistics. All

responding Salesperson EI means and standard deviations were calculated. Top and Bottom

Salesperson Global Trait EI scores were separated into two groups for further analysis. Averaged

mean and standard deviation of EI scores for Top vs. Bottom performing salespersons groups were

calculated and compared (See Table 4). Sales Performance was based on Sales Managers opinions

of their relevant sales staff. It was agreed by all sales managers that their assessment of Top and

Bottom performing salespersons is based closely on net profit generated for the firm, which is

usually related to income generated by the salesperson.

4. Lastly the difference between Top and Bottom Performing sales groups EI Means and EI

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Standard Deviations was analyzed. Firstly, a t-test for mean differences was performed, to test

whether there was a statistically significant difference between Top and Bottom Performing sales

groups EI Means. Secondly, a Levene‟s Test was performed to test whether there was a statistically

significant difference between Top and Bottom Performing sales groups EI Standard Deviations.

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RESEARCH FINDINGS, ANALYSIS AND DISCUSSION

3.6 Characteristics of the sample

Below in Table 1 is a representation of the demographic characteristics of the sample.

Table 1 - Demographics

Certain additional demographic characteristics were gathered from the 25 sales people surveyed in

this study. Initially 8 different sales managers at CPFS firms agreed to confidentially provide

names of their sales performers who performed exclusively in the Top & Bottom 20% within their

relevant sales teams. Sales performers falling in the „Middle‟ 60% of sales teams were ignored. 30

sales people (15 Top & 15 Bottom) were then emailed, of which 26 responses to this survey were

received. One survey response was disregarded, as it was considered an outlier.

A majority of the sample is made up of male respondents (64%), which is a commonly encountered

gender profile within the SAFS sales industry.

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A majority of the sample is made up of white respondents (64%), which is a commonly

encountered racial profile within the CPFS sales industry. Future studies might well consider

extending the race sample size, as well as studying for variable differences within particular race

groups.

The Mean Age is 35 years old, which is a commonly encountered age profile within the CPFS sales

industry. The youngest and oldest survey participants were 25 and 50 years old respectively.

Table 2 - EI results

As indicated in Table 2 above, total sample EI score for all respondents averaged 5.57 out of a

possible 7 on the Likert scale for the TEIQue-SF test. Standard deviation, Median, Maximum and

Minimum scores all appear reasonable. Reasonableness of these results will be discussed more in

Table 5 below.

Table 3 - Age characteristics

The Age mean and standard deviation of the Top 20% and Bottom 20% performing groups is very

similar. This would suggest the age make-up of either of these two groups, is not likely a factor

that influenced sales performance or the EI scores for comparison purposes. Future studies might

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well consider focussing on a larger data set of more older and younger sales people or less and

more experienced sales people, and gauging if this has a significant impact on sales performance.

Figure 5 - EI scores

Individual EI Scores of Top & Bottom performers

The results in Table 4 below indicate the Top 20% performing sales people have slightly higher

mean EI score than their Bottom 20% performing sales team counterparts. How strongly it can be

assumed this slightly higher average mean EI in Top performing salespeople influences sales

performance over Bottom performers will be discussed more the next section of this study.

Table 4 - EI results by category

0

50

100

150

200

TBBTBBTTBBTTBTTBTBTBTBBTT

EI Score

EI Score

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Table 5 below compares the EI results obtained from various TEIQue test studies with this study.

Table 5 – Comparative TEIQue studies

A Rodeiro, Bell and Emery (2009) study indicates a Population Norm mean (4.53) lower than the

comparative studies means represented in this study (See Table 5). This is plausible, because the

comparative means are all from sample groups (i.e. Financial Salespeople, Business Executives &

Sports Coaches) expected to have above average EI scores when compared to the average

population. The TEIQue EI data on South African Executives and Sports Coaches surveyed were

from a Lifson (2009) study.

Interestingly, the standard deviations of EI scores in this study are similar to that of the population

norm, Business Executives and Sports Coaches studies. This in some ways supports the validity of

data produced in this study.

3.7 Research Analysis and Discussion

As outlined in the Data Analysis Section in 3.5, the difference between Top and Bottom Performing

sales groups EI Means and Standard Deviations was analyzed. Firstly, a t-test to measure mean

differences was performed, to test whether there was a statistically significant difference between

Top and Bottom Performing sales groups EI Means. This test would determine if the Null

hypothesis is proven statistically significant or not in this study.

Secondly, a Levene‟s Test was performed to measure if there was a statistically significant

difference between Top and Bottom Performing sales groups EI Standard Deviations. If it is found

that there is a statistically significant difference in standard deviations between the two groups, this

may influence the validity of the t-test.

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The T-test examined the following hypothesis:

H0 : There is no difference in the EI means of Top vs. Bottom Performing Sales Groups at CPFS

firms.

H1 : There is a difference in the EI means of Top vs. Bottom Performing Sales Groups at CPFS

firms.

This hypothesis test was conducted at the 5% significance level.

A t statistic was calculated:

T = 0.53

At 5% level of significance with 48 degree of freedom the critical value is 2.048.

Thus, since 0.53<2.048, we accepted the null hypothesis and conclude that there is no significant

difference in means of Top vs. Bottom Performing Sales Groups at CPFS firms.

Levene‟s Test examined if there is a statistically significant difference between Top and Bottom

Performing sales groups EI Standard Deviations:

W is the result of the test,

k is the number of different groups to which the samples belong,

N is the total number of samples,

Ni is the number of samples in the ith group,

Yij is the value of the jth sample from the ith group,

is the mean of all Zij,

is the mean of the Zij for group i.

The significance of W is tested against F(α,k − 1,N − k) where F is a quantile of the F test

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distribution, with k − 1 and N − k its degrees of freedom, and α is the chosen level of

significance (usually 0.05 or 0.01).

A separate test was setup to gauge the standard deviations in EI means of Top and Bottom

Performing Sales Groups at CPFS firms.

A Levene‟s test Hypothesis was formed, for the purpose of main hypothesis validation:

H0: There is no difference in variances of standard deviations in EI means of Top and Bottom


H1: There is a difference in variances of standard deviations in EI means of Top and Bottom


The test statistic W=9.62

This research used the F-test distribution tables at 5% level of significance and v1 =1 and v2 = 23.

The critical value is 7.88 and since W is above than 7.88 H0 is accepted and it is concluded that

there is enough evidence that there is no significant differences in variances of standard deviations

in EI means of Top and Bottom Performing Sales Groups at CPFS firms. The fact that standard

deviations of the two groups EI‟s are not different serves to further validate the original hypothesis

finding that the Null Hypothesis is valid. Had this Levene‟s test indicated there is a significant

difference in the two group‟s standard deviations, this would have made the main hypothesis

weaker.

3.8 Research Limitations

A main limitation of this study is the sample size. Due to a limited sample size of twenty-five sales

people, it needs to be considered there could be a reduction of correctness of the sample that

consequently results in increased sampling error (Bryman & Bell, 2007). This is a concern as the

smaller sample may have a direct impact on the reliability of the study results.

A further potential limitation is the choice of the TEIQue EI measuring instrument used in this

study. There is much debate around which EI measuring instrument is „best‟, and new

developments surrounding EI testing measures occur regularly. In addition, TEIQue was developed

in the United Kingdom, not South Africa. As a result there is a need to test around the possible

cross-cultural differences with regard to the test and construct in order to assure this test is reliable

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in a South African context. Another limitation regarding the use of the TEIQue test is the limited

previous studies available of TEIQue reported EI scores linked to sales performance.

The TEIQue assessment is a self-report test. It should be considered there is support for the

argument that self-report measures provide a measure of the candidate‟s self-concept rather than

their actual ability or traits (Bailie & Ekermans, 2006) and are therefore associated with self-report

biases (Stein, Papadogiannis, Yip & Sitarenios, 2009).

Another criticism of self-report assessments is „socially desirable responding‟. In these cases test-

takers characterize themselves with an excessive positive bias (Paulhus & Delroy, 1991). This

favoritism has long been known to contaminate some responses on personality inventories (Holden,

2007).

Another limitation of this study is the lack of significant difference between the two groups. It is

possible to assume that the two groups (Top 20% and Bottom 20% sales performers) are not

significantly different enough to draw strong conclusions. There is sample data to suggest that both

sales people groups have above average EI levels compared to population norms (See Table 5

above). It is plausible that Top performing sales people attained their superior performance due to

reasons other than their EI score exclusively. A possible suggestion to better analyze this question

would be for future studies to survey CPFS sales people who „dropped‟ out of the field. This data

might produce more distinctly different EI results, and thereby add to the academic research in this

area.

Finally, it is possible that unforeseen factors in addition to EI impacting on the success level of

salespeople have not been uncovered by this study. These additional features that possibly impact

on sales performance need to be considered in addition to EI levels. For example, a minimum of 5

years financial sales experience was set in this study. However the number of years of financial

sales experience data was not captured in this study. It is quite plausible that a salespersons

performance would benefit from many years of financial sales experience and a large network of

customers, even if that particular salesperson did not have a high EI score. Similarly, the levels of

post high school education might have a similar positive impact on sales performance, independent

of EI levels. These are areas for future research to consider.

From a resource perspective, no budget was applied for this study. Given that this is an MBA

thesis where this researcher also has full time job, this somewhat limits the amount of data

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gatherable and requires the use of a free test to collect data.

4 RESEARCH CONCLUSIONS

The goal of this study is to investigate the possible link between higher EI scores and higher

performing salespersons at CPFS firms. Much research has been conducted on features of top

performing salespeople, who achieve superior sales performance in relation to their peers.

Variables‟ determining sales performance has interested marketing researchers for a long time.

Some of these variables previously studied making up EI and having a significant influence on

sales performance are Empathy, Self-Motivation, Self-Regulation. Since these variables

influencing sales performance are central to EI, it is reasonable to suppose a higher EI score is a

factor that will result in improved sales performance.

The results of this study indicate from a casual observation perspective, the average EI level of Top

performing salespeople at CPFS firms was slightly higher (2.9%) than lower performing sales peers

when measured using TEIQue. However, more importantly this study also found from an academic

statistical perspective after using a t-test at 5% significance level, that EI levels of salespeople were

not significantly related to superior sales performance. This said, previous related academic

research has indicated to the contrary, that EI does significantly impact sales performance. As

noted in the research limitations above, a main concern with this study was the limited data set. In

the researcher‟s opinion, this may have impacted the results of this study.

It is theorized EI affects several workplace circumstances including sales performance. However,

being a relatively new field, EI is a variable without a great body of academic research conducted

of its impact on sales performance. This type of academic research is also especially lacking in

emerging market settings, with a majority of existing studies limited to developed markets. EI-Sales

performance research such as this study is also particularly lacking with regards to research using

the Trait TEIQue EI measurement method. Thus, this research contributes to all these bodies of

limited of existing academic literature.

This study has also produced a list of potentially useful future research suggestions (See Section 5 –

Future Research Directions). These suggestions may well assist future studies in the relatively new

domain of EI-Sales performance related field.

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5 FUTURE RESEARCH DIRECTIONS

Based on the limitations listed above in section 4.3, various recommendations can be made for

future research.

Firstly, replications of a larger data sample should be performed to determine whether the scales

used in this research are valid and reliable. Simply put, more CPFS firms should be surveyed. In

addition, including a new category of „Failed Sales Persons‟ should be considered, to gauge how

their EI and additional variables compare to surveyed Top performing salespeople. Such future

research on Failed Sales Persons might reflect a greater difference in EI values when compared

with Top Sales people. This research might also assist us better understand why salespeople fail.

Future research might also consider „re-testing‟ previously surveyed participants (e.g. 12 months

after initial testing), to gauge respondent feedback variance over time.

Additionally, future research should deliberate what additional questions the demographic

questionnaire following the TEIQue survey should contain. The appropriate additional questions

might reveal unforeseen factors that impact on the success level of salespeople. These additional

features that possibly impact on sales performance will need to be considered in addition to EI

levels. For example, a minimum of 5 years financial sales experience was set in this study. Future

studies might include the following questions to access variables that possibly impact sales level of

performance in addition to EI. „How many years of financial sales experience do you have?‟; „How

many years of post high school education do you have?‟ These additional variables data can be

studied, and judged if they impact sales performance.

To reduce self-report bias in future studies, EI results might also be assessed by other people (e.g.

fellow sales staff/sales manager/customers). This would likely lead to a more valid data set.

In future studies, EI could be compared to other characteristics that have in the past been analyzed

in sales research, E.g. Empathy, self/other orientation etc. To study such characteristics, future

research might benefit from replicating this study with the longer TEIQue v. 1.50 (153 items, 15

facets, 4 factors, global trait EI score) EI test. Although it takes survey participants longer to

complete (approximately 30 minutes) such a test will also reveal 15 EI subscales (e.g. Self Esteem,

Self Expression, Happiness, Empathy etc.).

Finally, it would be interesting to study sales fields other than the financial services sector. Cote

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and Miners (2006) suggest that the relationship between EI and job performance becomes more

positive as cognitive intelligence decreases. This idea was originally proposed in the context of

academic performance (Petrides, Frederickson, & Furnham, 2004). The results of the former study

supports the model that employees with lower IQ‟s obtain higher task performance, the higher their

EI. The competence levels (and likely IQ levels) of current survey participants in the CPFS industry

is generally higher than average. Therefore, this may have led to a lowering of the impact of EI on

sales performance, than if sales people in a different field with lower IQ‟s were studied.

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APPENDICES

Appendix 1 – TEIQue-SF EI test & Amended Demographics questionnaire:

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Demographics Questionnaire:

Please complete the following, by circling/completing:

1. What is your sex?

a. Male

b. Female

2. What is your birth year?

a. 19……

3. How would you describe yourself ethnically?

a. Black

b. Colored

c. White

d. Other

4. My name is: …………. ……………

Trait Emotional Intelligence Questionnaire – Short Form (TEIQue-SF). This is a 30-item

questionnaire designed to measure global trait emotional intelligence (trait EI). It is based on the

long form of the TEIQue (Petrides, 2001).

For more information about the trait emotional intelligence research program go to:

www.psychometriclab.com


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Appendix 2 - TEIQue-SF scoring template

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Appendix 3 – TEIQue-V 1.50 EI test & Full Demographics questionnaire:

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Appendix 4 – Adjusted square correlation coefficients for predicting EI

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Appendix 5 – TEIQue v1.50 results grid

Appendix 6 – Survey raw data

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Appendix 7 – Suggestions to improve EI

The writer of this study does not possess any formal training in psychology.

Below is a list of references readers may consider if they wish to increase their own or their staff’s

EI scores.

EI websites

www.eiconsortium.org

www.eqi.org

www.unh.edu/emotional_intelligence

Basics EI books for individuals

Emotional Discipline (2003) by Charles C. Manz

Handbook of emotional intelligence(2000) by Boyatzis, Goleman & Rhee.

Basic EI books for the workplace

Working with emotional intelligence (1998) by Goleman.

Executive EQ: Emotional Intelligence in Leadership and Organizations (1997) by Cooper & Sawaf.

Emotional Intelligence at Work (1998) by Hendrie Weisinger

Academic papers on EI improvement

Nelis, D., Quoidbach, J., Mikolajczak, M., & Hansenne, M. (2009). Increasing emotional

intelligence: (How) is it possible? Personality and Individual Differences, 47, 36-41.

Sojka, J., & Deeter-Schmelz, D. (2002). Enhancing the Emotional Intelligence of Salespeople. Min-

American Jouranal of Business , 43-48.

http://www.eiconsortium.org/

http://www.eqi.org/

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Source: (Salovey & Mayer, 1990)

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