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Is there a link between personality, emotions and sales performance?
Abstract
This research examines how a salesperson's personality and the emotions he/she displays during a sales conversation are related, how both are related to buyers' evaluations of the seller, and whether there is an interaction between personality and emotions. Based on data from 63 role-played sales conversations that were analyzed using automated facial recognition, as well as pre-and post-questionnaires, our findings indicate that openness and agreeableness seem to be particularly relevant personality traits with regards to subjective sales performance. Furthermore, overall engagement, expressions of joy, and surprisingly also anger, are positively related to buyer evaluations of the seller. Finally, we found that the emotion of joy positively interacts with agreeableness, but negatively interacts with openness, in influencing buyers' perceptions of the seller.
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Selling skills are learned proficiency at performing tasks necessary for a sales job. They are among the most important predictors of sales performance. However, the research into selling skills has been hampered by the lack of an overall scale. To address this shortcoming the present paper identifies a model of sales skills consisting of three components of interpersonal skills, salesmanship skills, and technical skills. Using exploratory and confirmatory factor analysis, the authors report the development of a Selling Skill scale as a reliable and valid instrument. The authors suggest priorities for future research and potential uses of this instrument.
The Revised NEO Personality Inventory (NEO PI-R; Costa & McCrae, 1992a) is a questionnaire measure of 30 traits that define the comprehensive five-factor model (FFM) of personality. Data from police selection, college student, and Hispanic American samples illustrate the psychometric properties of the instrument. In vocational counseling, the NEO PI-R can supplement measures of vocational interests and abilities, especially by calling attention to the client's strengths and weaknesses in adjustment and motivation. Use of the NEO Job Profiler, a tool designed to help identify the personality requirements of different occupations, is illustrated in the police selection sample. Together, the NEO Job Profiler and NEO PI-R can help determine the optimal match between person and occupation.
This article develops a theory that explains how and when emotions, produced by social exchange, generate stronger or weaker ties to relations, groups, or networks. It is argued that social exchange produces positive or negative global feelings, which are internally rewarding or punishing. The theory indicates that social units (relations, groups, networks) are perceived as a source of these feelings, contingent on the degree of jointness in the exchange task. The jointness of the task is greatest if (1) actors find it difficult to distinguish their individual effects on or contributions to solving the exchange task (nonseparability) and (2) actors perceive a shared responsibility for success or failure at the exchange task. The theory explicates the effects of different exchange structures on these conditions and, in turn, on cohesion and solidarity. Implications are developed for network-to-group transformations.
Theorists have argued that facial expressions of emotion serve the interpersonal function of allowing one animal to predict another's behavior. Humans may extend these predictions into the indefinite future, as in the case of trait inference. The hypothesis that facial expressions of emotion (e.g., anger, disgust, fear, happiness, and sadness) affect subjects' interpersonal trait inferences (e.g., dominance and affiliation) was tested in two experiments. Subjects rated the dispositional affiliation and dominance of target faces with either static or apparently moving expressions. They inferred high dominance and affiliation from happy expressions, high dominance and low affiliation from angry and disgusted expressions, and low dominance from fearful and sad expressions. The findings suggest that facial expressions of emotion convey not only a target's internal state, but also differentially convey interpersonal information, which could potentially seed trait inference.
This study tested the hypothesis derived from ecological theory that adaptive social perceptions of emotion expressions fuel trait impressions. Moreover, it was predicted that these impressions would be overgeneralized and perceived in faces that were not intentionally posing expressions but nevertheless varied in emotional demeanor. To test these predictions, perceivers viewed 32 untrained targets posing happy, surprised, angry, sad, and fearful expressions and formed impressions of their dominance and affiliation. When targets posed happiness and surprise they were perceived as high in dominance and affiliation whereas when they posed anger they were perceived as high in dominance and low in affiliation. When targets posed sadness and fear they were perceived as low in dominance. As predicted, many of these impressions were overgeneralized and attributed to targets who were not posing expressions. The observed effects were generally independent of the impact of other facial cues (i.e., attractiveness and babyishness).
The face provides an important channel for communicating affect valence, the positive or negative emotional charge of an experience. This paper addresses the challenging pattern recognition problem of assigning affect valence labels (positive, negative or neutral) to facial action sequences obtained from unsegmented videos coded using the Facial Action Coding System (FACS). The data were obtained from viewers watching eight short movies with each second of video labeled with self-reported valence and hand coded using FACS. We identify the most frequently occurring Facial Actions and propose the usefulness of a Facial Action Unit Spectrogram. We compare both generative and discriminative classifiers on accuracy and computational complexity: Support Vector Machines, Hidden Markov Models, Conditional Random Fields and Latent-Dynamic Conditional Random Fields. We conduct three tests of generalization with each model. The results provide a first benchmark for classification of self-report valences from spontaneous expressions from a large group of people (n = 42). Success is demonstrated for increasing levels of generalization and discriminative classifiers are shown to significantly outperform generative classifiers over this large data set. We discuss the challenges encountered in dealing with a naturalistic dataset with sparse observations and its implications on the results.
In the increasingly user-generated Web, users’ personality traits may be crucial factors leading them to engage in this participatory media. The literature suggests factors such as extraversion, emotional stability and openness to experience are related to uses of social applications on the Internet. Using a national sample of US adults, this study investigated the relationship between these three dimensions of the Big-Five model and social media use (defined as use of social networking sites and instant messages). It also examined whether gender and age played a role in that dynamic. Results revealed that while extraversion and openness to experiences were positively related to social media use, emotional stability was a negative predictor, controlling for socio-demographics and life satisfaction. These findings differed by gender and age. While extraverted men and women were both likely to be more frequent users of social media tools, only the men with greater degrees of emotional instability were more regular users. The relationship between extraversion and social media use was particularly important among the young adult cohort. Conversely, being open to new experiences emerged as an important personality predictor of social media use for the more mature segment of the sample.
Emotional expressions influence social judgments of personality traits. The goal of the present research was to show that it is of interest to assess the impact of neutral expressions in this context. In 2 studies using different methodologies, the authors found that participants perceived men who expressed neutral and angry emotions as higher in dominance when compared with men expressing sadness or shame. Study 1 showed that this is also true for men expressing happiness. In contrast, women expressing either anger or happiness were perceived as higher in dominance than were women showing a neutral expression who were rated as less dominant. However, sadness expressions by both men and women clearly decreased the extent to which they were perceived as dominant, and a trend in this direction emerged for shame expressions by men in Study 2. Thus, neutral expressions seem to be perceived as a sign of dominance in men but not in women. The present findings extend our understanding of the way different emotional expressions affect perceived dominance and the signal function of neutral expressions-which in the past have often been ignored.
We present a real-time system for detecting facial action units and inferring emotional states from head and shoulder gestures and facial expressions. The dynamic system uses three levels of inference on progressively longer time scales. Firstly, facial action units and head orientation are identified from 22 feature points and Gabor filters. Secondly, Hidden Markov Models are used to classify sequences of actions into head and shoulder gestures. Finally, a multi level Dynamic Bayesian Network is used to model the unfolding emotional state based on probabilities of different gestures. The most probable state over a given video clip is chosen as the label for that clip. The average F1 score for 12 action units (AUs 1, 2, 4, 6, 7, 10, 12, 15, 17, 18, 25, 26), labelled on a frame by frame basis, was 0.461. The average classification rate for five emotional states (anger, fear, joy, relief, sadness) was 0.440. Sadness had the greatest rate, 0.64, anger the smallest, 0.11.
The term “affect” is generally used to refer to a set of “internal feeling states,” and includes mood and emotion. This paper provides an assessment of the current state of knowledge on affect and other related constructs as they relate to personal selling and sales management. The authors review and reflect on the theoretical frameworks commonly used in the study of affect in the sales literature. The managerial issues related with affect in sales contexts are also highlighted. The authors conclude with an identification of critical gaps that exist in the sales literature and suggest several directions for future research. © 2013 PSE National Educational Foundation. All rights reserved.
Most computer models for the automatic recognition of emotion from nonverbal signals (e.g., facial or vocal expression) have adopted a discrete emotion perspective, i.e., they output a categorical emotion from a limited pool of candidate labels. The discrete perspective suffers from practical and theoretical drawbacks that limit the generalizability of such systems. The authors of this chapter propose instead to adopt an appraisal perspective in modeling emotion recognition, i.e., to infer the subjective cognitive evaluations that underlie both the nonverbal cues and the overall emotion states. In a first step, expressive features would be used to infer appraisals; in a second step, the inferred appraisals would be used to predict an emotion label. The first step is practically unexplored in emotion literature. Such a system would allow to (a) link models of emotion recognition and production, (b) add contextual information to the inference algorithm, and (c) allow detection of subtle emotion states.
This meta-analysis evaluated predictors of both objective and subjective sales performance. Biodata measures and sales ability inventories were good predictors of the ratings criterion, with corrected rs of .52 and .45, respectively. Potency (a subdimension of the Big 5 personality dimension Extraversion) predicted supervisor ratings of performance (r =.28) and objective measures of sales (r =.26). Achievement (a component of the Conscientiousness dimension) predicted ratings (r =.25) and objective sales (r=.41). General cognitive ability showed a correlation of .40 with ratings but only .04 with objective sales. Similarly, age predicted ratings (r =.26) but not objective sales (r = -.06). On the basis of a small number of studies, interest appears to be a promising predictor of sales success.
While we have known for centuries that facial expressions can reveal what people are thinking and feeling, it is only recently that the face has been studied scientifically for what it can tell us about internal states, social behavior, and psychopathology. Today's widely available, sophisticated measuring systems have allowed us to conduct a wealth of new research on facial behavior that has contributed enormously to our understanding of the relationship between facial expression and human psychology. The chapters in this volume present the state-of-the-art in this research. They address key topics and questions, such as the dynamic and morphological differences between voluntary and involuntary expressions, the relationship between what people show on their faces and what they say they feel, whether it is possible to use facial behavior to draw distinctions among psychiatric populations, and how far research on automating facial measurement has progressed. © 1997, 2005 by Oxford University Press, Inc. All rights reserved.
The concept of customer orientation in salespeople is defined, a scale is developed to measure the degree to which salespeople engage in customer-oriented selling, and the properties of the scale are reported. A test of the nomological validity indicates the use of customer-oriented selling is related to the ability of the salespeople to help their customers and the quality of the customer-salesperson relationship.
Behavioral research on negotiation in recent years has been dominated by the decision-making research paradigm, which accords a relatively narrow role to emotions. Decision-making researchers have considered emotions primarily in terms of how an individual's positive or negative affect impacts, and usually impedes, his or her information processing. Drawing on recent advances in psychology and other fields, we propose an alternative perspective that highlights more social and more functional aspects of emotion in negotiation. We conceptualize emotions as interpersonal communication systems that help individuals navigate the basic problems that arise in dyad and group relations. Emotions are evoked by these specific relational problems and one person's emotional expression impacts other persons, often with the consequence of resolving the relational problem. From this social functional perspective, we draw insights concerning: (a) the influence of specific emotions upon negotiation-related cognition and behavior; (b) the transitions between qualitatively different phases within negotiations; and (c) the ways in which negotiations are shaped by contextual variables such as culture and communication media.
This study investigated the relation of the "Big Five" personality di- mensions (Extraversion, Emotional Stability, Agreeableness, Consci- entiousness, and Openness to Experience) to three job performance criteria (job proficiency, training proficiency, and personnel data) for five occupational groups (professionals, police, managers, sales, and skilled/semi-skilled). Results indicated that one dimension of person- ality. Conscientiousness, showed consistent relations with all job per- formance criteria for all occupational groups. For the remaining per- sonality dimensions, the estimated true score correlations varied by occupational group and criterion type. Extraversion was a valid pre- dictor for two occupations involving social interaction, managers and sales (across criterion types). Also, both Openness to Experience and Extraversion were valid predictors of the training proficiency criterion (across occupations). Other personality dimensions were also found to be valid predictors for some occupations and some criterion types, but the magnitude of the estimated true score correlations was small (p < .10). Overall, the results illustrate the benefits of using the 5- factor model of personality to accumulate and communicate empirical findings. The findings have numerous implications for research and practice in personnel psychology, especially in the subfields of person- nel selection, training and development, and performance appraisal.
Discusses research on facial expressions of emotion and presents suggestions for recognizing and interpreting various expressions. Using many photographs of faces that reflect surprise, fear, disgust, anger, happiness, and sadness, methods of correctly identifying these basic emotions and of understanding when people try to mask or simulate them are outlined. Practice exercises are also included. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The goal of this research was to investigate the impact of nonverbal expressive cues on the attribution of the Big Five personality traits. Expressive cues of fear, disgust, happiness, and sadness were elicited in a sample of 22 encoders while watching films, narrating, and posing. Encoders’ personalities were rated by themselves and unacquainted raters who watched the encoders, and blind judges rated the traits of a typical student. Expressive cues influenced the raters’ attribution of personality, but this influence was weakest when the encoders expressed happiness (vs. negative emotions) and when they were narrating an emotional experience (when the cues were least potent). Negative and strong expressive cues interfered with the application of a normative, and more accurate, judgment strategy.
When emotions run amok, negotiators lose perspective and make serious mistakes or perform poorly. The authors describe emotions, explore their origins, detail their physiology, demonstrate their key role in human behavior (particularly in negotiation), and propose a series of recommendations for dealing with fear and anger, two critical emotions in negotiations.
As we begin the new millennium, it is an appropriate time to examine what we have learned about personality-performance relationships over the past century and to embark on new directions for research. In this study we quantitatively summarize the results of 15 prior meta-analytic studies that have investigated the relationship between the Five Factor Model (FFM) personality traits and job performance. Results support the previous findings that conscientiousness is a valid predictor across performance measures in all occupations studied. Emotional stability was also found to be a generalizable predictor when overall work performance was the criterion, but its relationship to specific performance criteria and occupations was less consistent than was conscientiousness. Though the other three Big Five traits (extraversion, openness and agreeableness) did not predict overall work performance, they did predict success in specific occupations or relate to specific criteria. The studies upon which these results are based comprise most of the research that has been conducted on this topic in the past century. Consequently, we call for a moratorium on meta-analytic studies of the type reviewed in our study and recommend that researchers embark on a new research agenda designed to further our understanding of personality-performance linkages.
We examined whether the discrete, other-directed emotions of anger and compassion exert a greater influence on negotiations than mood. Drawing on cognitive appraisal theories of emotion, we specifically tested whether negotiators who felt high anger and low compassion for each other would (1) have less desire to work with each other in the future, (2) achieve fewer joint gains, and (3) successfully claim more value for themselves than negotiators who had more positive emotional regard for the other party. The results of a mixed-motive simulation experiment confirmed the first two predictions but not the last. The results confirmed that anger and compassion exerted a greater influence than mood. These findings indicate why prior advice stemming from the conflict and negotiation literature for managing anger has been counterproductive and suggest contrasting prescriptions.
In the latest decades, emotions have become an important research topic in all behavioral sciences, and not the least in advertising. Yet, advertising literature on how to measure emotions is not straightforward. The major aim of this article is to give an update on the different methods used for measuring emotions in advertising and to discuss their validity and applicability. We further draw conclusions on the relation between emotions and traditional measures of advertising effectiveness. We finally formulate recommendations on the use of the different methods and make suggestions for future research.
Two studies provided evidence that bolsters the Marsh, Adams, and Kleck hypothesis that the morphology of certain emotion expressions reflects an evolved adaptation to mimic babies or mature adults. Study 1 found differences in emotion expressions' resemblance to babies using objective indices of babyfaceness provided by connectionist models that are impervious to overlapping cultural stereotypes about babies and the emotions. Study 2 not only replicated parallels between impressions of certain emotions and babies versus adults but also showed that objective indices of babyfaceness partially mediated impressions of the emotion expressions. babyface effects were independent of strong effects of attractiveness, and babyfaceness did not mediate impressions of happy expressions, to which the evolutionary hypothesis would not apply.