TY - JOUR
AU - Eriksson,, Niklas
AB - Abstract This article responds to a call for research on the context-specific effects of human images in different online contexts. This study investigates how inherent facial expressions in a consultant’s profile image influence the likelihood to contact tendency of small business-to-business website visitors. The results from a conjoint study (n = 67) demonstrate that a consultant’s profile image with a smiling facial expression induced a higher likelihood to contact tendency. While the absence of a profile image reduced this tendency, relatively more than an image with a neutral facial expression. In light of these results, implications for small businesses as well as suggestions for future research are discussed. RESEARCH HIGHLIGHTS Facial expressions in a consultant’s profile image influence customers in online B2B contexts. Facial expressions were the most important stimuli that encourage initial contact from customers. Smiling facial expressions had a positive impact on the likelihood to contact tendency. Absence of a profile image reduced the likelihood to contact. Human facial expressions can be used as a design element to positively influence visitors. 1. INTRODUCTION Corporate websites have become one of the primary tools used by small businesses to communicate with potential customers. According to a recent survey by Google and Millward Brown Digital (Snyder and Hilal, 2015), 89% of respondents are using the Internet for business-to-business (B2B) research purposes. Moreover, the survey highlights that 71% of B2B researchers use a generic search and conduct 12 searches before engaging on a specific brand’s website. This indicates that opportunities might be equal for small and large B2B organizations. Interestingly, the report further specifies that digitally native millennials comprise nearly half of the aforementioned B2B audience now (Snyder and Hilal, 2015). It is safe to assume that e-commerce is a universally accepted (and expected) way to conduct B2B exchanges in the 21st century. B2B websites often become the first point of interaction between prospective buyers and sellers. Thus, elements of B2B websites become crucial influencing factors which warrant further examination. B2B decision-making is considered to be inherently more complex when compared to business-to-consumer (B2C) contexts (Fill, 2005; Kotler and Pfoertsch, 2006). Organizational buying procedures are comprised of relatively longer decision processes that generally involve more than one person (Fill, 2005; Solomon, 2009). Recent reports show that while C-suite and senior-level executives have final authority on purchase decisions, 81% of the non-C-suiters influence B2B decisions (Snyder and Hilal, 2015). B2B environments have been targeted with marketing approaches that differ considerably from the average B2C marketing efforts. Traditionally, B2B customers are often thought of as being more ‘rational’ than B2C customers. Therefore, B2B companies emphasize the practical traits of a product and its superior value. Marketing tactics directed toward B2B customers implement a more information-oriented or functional approach in their efforts (Fill, 2005; Lynch and De Chernatony, 2004). However, disruptive signs show that B2B marketing strategies are now being modified to use tactics similar to those used in B2C marketing (Kotler and Pfoertsch, 2006; Lynch and De Chernatony, 2004). Therefore, examining the influence of ‘non-functional’ components, such as profile images, are deserving of research attention in certain B2B contexts. As mentioned earlier, complexity is a characteristic attribute of B2B environments. This raises challenges in marketing the quality of B2B services. Service quality is difficult to evaluate in B2B environments (Virtsonis and Harridge-March, 2008). Management consulting firms provide specialized services in the form of knowledge and expertise. As a result, the quality of intangible services (that a consultant might provide) might be more difficult to assess (for customers), even after the service has been rendered (Von Nordenflycht, 2010). Based on some of the mechanisms described by Von Nordenflycht (2010), appearance is one of the ways firms can signal the quality of their services. This refers to the observable characteristics of the firm’s employees (professional experience, educational attainment, physical appearance, etc.). Facial expressions are often classified as observable indicators of underlying affective states (Ekman and Friesen, 1971; Izard, 1997), which can have subsequent influences on the perceiver (Marsh et al., 2005; Stins et al., 2011). Other common observable characteristics such as educational attainment and professional experience are basic qualifications for management consultants in European and US regions (Gross and Poor, 2008). Therefore, these observable characteristics were operationalized in this study (profile images and the inherent facial expressions, educational level and professional experience). Previous research on online environments demonstrate that incorporating human facial images implies social presence, and assists in building trust (Aldiri et al., 2008; Fogg et al., 2001; Steinbrück et al., 2002). Cyr et al. (2009) examined how the presence of human images influenced the perception of websites. They found that the presence of human images indicated social presence and can incite positive affect. However, as far as we know, previous studies examining the influence of human images and its subsequent impact on user behavior have not been conducted in B2B website contexts (Aldiri et al., 2008; Fagerstrøm et al., 2017). Furthermore, Cyr et al. (2009) state that generalizations across contexts should not be made without investigation, as effects of facial images might be context-dependent. Since B2B customers use corporate websites to collect and examine information to facilitate decision-making (Virtsonis and Harridge-March, 2008), elements like profile images can potentially have a significant impact in B2B contexts. The contribution of this research resides in examining factors that can influence conversion rates for small B2B firms. This study investigates how a consultant’s profile image and its facial expressions affect a user’s likelihood to contact small B2B consultants online. 2. LITERATURE REVIEW Research in environmental psychology has utilized the stimuli-organism-response (S-O-R) framework to examine how behaviors are influenced by physical environments. Based on this paradigm, a model originally conceptualized by Mehrabian and Russell (1974) has been used extensively in management-oriented literature (especially retail) (Baker et al., 1994; Bitner, 1992; Donovan et al., 1994). Within this model, environmental variables are identified as the main reasons for people’s context-specific approach-avoidance behaviors (Mehrabian and Russell, 1974; Russell and Mehrabian, 1978). Internal states mediate the relationship between the environment and approach-avoidance behavior. Naturally, as this area of research progressed, the atmospheric influences of websites attracted the interest of researchers and practitioners. Eroglu et al. (2001) used a similar conceptual stance and the S-O-R framework to study the effect of atmospheric elements in the online stores. They operationalized online atmospheric cues as the ‘stimuli’, shoppers’ internal states (affective or cognitive) as the ‘organism’, and approach-avoidance behaviors as the ‘response’ (Eroglu et al., 2001; 2003). Just as physical environments may invite or discourage interaction through their physical design, the same reasoning can be applied to study website design characteristics (Clark et al., 2009). An adaptation of the atmospherics models proposed by Mehrabian and Russell (1974) and Eroglu et al. (2001) was used as the conceptual basis for the present study. As highlighted by Donovan and Rossiter (1982), communication-related approach-avoidance behaviors can take the form of ‘a desire or willingness to communicate with others in the environment (approach), as opposed to a tendency to avoid interacting with others or to ignore the communication attempts from others (avoidance)’. Therefore, we used ‘likelihood to contact’ the B2B consultant as the dependent variable in this study. Additionally, we do not speculate about the complex interactions and/or interconnections between internal processes (emotion, cognition, perception, learning, memory, motivation, etc.) affecting subsequent responses. Furthermore, diverging from previous studies, we propose that approach or avoidance tendencies should be considered as an additional internal factor (organism). This allows us to generate assumptions about the effect of (internal) approach-avoidance tendencies on the dependent variable of ‘likelihood to contact’. 2.1. Facial expressions—positive and neutral Research suggests two different perspectives for why facial expressions have evolved as a form of nonverbal communication. The prevailing, traditional hypothesis views facial expressions as signals of internal emotional states. Empirical cross-cultural studies provide support for the universality hypothesis which suggests that certain emotions are universally perceived from the facial expressions (Ekman, 1994; Ekman and Friesen, 1971; Izard, 1994). This line of thought conceptualizes internal affect as a set of 5–9 discrete, basic categorical or fundamental emotions (such as joy/happiness, sadness, fear, surprise, anger and disgust) that are shared by humans everywhere. The underlying assumptions are that these basic emotions are universal in humans and these emotions can be conveyed in facial expressions (e.g. smiles are recognized as joy/happiness, scowls as anger, etc.). Evidence of this can be seen in a meta-analysis by Elfenbein and Ambady (2002), in which they found that emotions from facial expressions were universally recognized quite accurately and this accuracy increases when emotions are both expressed and recognized by in-group members. However, the universality hypothesis has been challenged by recent studies that have shown that perception of emotion from facial expressions are not actually ‘universal’ in the true sense of the word (Crivelli et al., 2017; Crivelli, Jarillo, et al., 2016; Crivelli, Russell, et al., 2016; Gendron et al., 2014; Jack et al., 2009; Jack et al., 2012). This supports the current trend in emotion research which considers emotion perception as actively constructed by perceivers to fit the social and physical constraints of their cultural domains (Gendron, 2017). Whether facial expressions signal emotions or not is still a subject of debate within academia. If the primary function of facial expressions is not to display emotion, then what could be the significance for their evolution? The alternate behavioral ecology hypothesis proposes that facial expressions are social signaling tools which help navigate our social encounters (Fridlund, 2014). In other words, facial expressions do not reflect internal states such as emotions, but are additional, dynamic signs used in social interactions. Facial expressions are used as the main signs of contingent action in social negotiation, and how they function depends upon the context of the current social interaction, the interactants and their interaction histories (Crivelli and Fridlund, 2018). Based on these two lines of thought regarding facial expressions, there are some takeaways we can use from both perspectives to examine the influence of facial expressions in profile images. All things considered, a few inferences can be made: (i) facial expressions have a cultural and contextual component that mediates their influence; (ii) facial expressions of emotions might not be universal, but they can be assumed to have a similar impact on average (especially in developed, societies), therefore signals are decoded relatively well by humans; (iii) facial expressions as a phenomena entail a mixture of innate and conditioned components; and (iv) facial expression have a signaling value (social and/or emotional), thus are an important component of social interactions. In this study, we focus on the impact of the facial expressions in a consultant’s profile image. Public social networking websites are popular stages for more self-expressive behaviors when compared to professional networking sites (Van Dijck, 2013). It would be reasonable to expect that profile images on B2B websites would be relatively more formal when compared to profile images used on public social networking websites. Most often, these are posed photographs taken professionally. In addition, one would also expect to see a narrower spectrum of facial expressions in such professional online contexts. Studies show that on corporate websites, users predominantly post profile images with either smiling or neutral facial expressions (Cardon et al., 2018; Tifferet and Vilnai-Yavetz, 2018). Thus, for ecological validity, we focus only positive and neutral facial expressions as others would seem too artificial in this context. Generally, smiling facial expressions are used as signs of happiness. The association of smiles with positive affective states encourages favorable perceptions in observers. Hareli et al. (2009) state that the demonstration of certain emotional expressions leads others to attribute specific traits to the individuals who express these emotions and, conversely, the knowledge that a person has certain traits leads people to expect certain emotional reactions from them. A study by Otta et al. (1994) clearly exemplifies this, as they found that stimulus images of smiling individuals resulted in favorable personality trait judgments by participants. The smiling facial expressions had a positive influence on the perceptions of observers. Similarly, several studies demonstrate that, in social contexts, the human smile is considered as a possible indicator of many prosocial qualities (Hess et al., 2000; Knutson, 1996). Since a smiling individual is evaluated positively, observers may assume that the person is socially approachable, which might encourage possible interaction. Smiling facial expressions would, therefore, influence approach-avoidance related tendencies. Stins et al. (2011) conducted an experiment to test the influence of angry and smiling facial expressions (as social cues) on the tendency of people to approach or avoid the stimuli (by postural body movements). They found that participants needed less time to initiate a forward step toward smiling faces than toward angry faces. Taken together, these studies suggest that a smiling facial expression positively influences observers’ expectations of certain emotional reactions, social characteristics and collaborative behaviors. While most facial expressions are associated with certain emotions, a neutral facial expression is considered to signify non-emotional reactions to stimuli. A neutral expression can also imply deliberate self-control of emotions (Schneider et al., 2013). In a study by Hareli et al. (2009), the participants perceived men who expressed neutral and angry emotions as higher in dominance when compared with men expressing sadness or shame. This dominance effect held only for men displaying angry and neutral expression and not for women displaying the same emotions (Hareli et al., 2009). This study also represents the common procedure used in facial expression research that utilizes neutral facial expressions as a point of comparison with emotive facial expressions (e.g. happiness, sadness, anger and fear expressions). These comparisons are used to examine the impact of certain expressions in different social contexts regarding different psychological phenomena. Many studies have contrasted the effects of smiling versus neutral facial expressions. Scharlemann et al. (2001) found that subjects were less likely to trust photographs of the same persons displaying neutral expressions versus smiling expressions. LaFrance and Hecht (1995) found that targets displaying smiling facial expressions received more lenient judgments than neutral targets. The perception of the target as a trustworthy person best accounted for this effect. Relative to each other, neutral and smiling facial expressions clearly have an opposing effect on the perception and judgments of individuals. Krumhuber et al. (2007) found that in a game of trust, a neutral expression (compared to authentic and fake smiles) was rated as least trustworthy. In a similar vein, Mussel et al. (2013) conducted a study using an ultimatum game in which they found that proposers with a smiling facial expression were more often accepted, compared to proposers with a neutral facial expression. In these cases, the contrasting effects of smiling and neutral facial expressions influenced the behaviors of the participants. From the above discussion, we can conclude that smiling faces would most likely reduce avoidance tendencies in terms of physical contact. These tendencies might not manifest physically in the virtual context but might hold true for other forms of contact such as communication attempts. A smiling expression would have a positive influence on the perceptions of observers that would probably result in favorable judgments and behaviors. Therefore, we can expect that a smiling facial expression would most likely evoke approach and abate avoidance tendencies and simultaneously increase the likelihood to contact. Thus, the first assumption of the study is: A1: A profile image with a positive facial expression will increase the tendency of the user’s likelihood to contact the small B2B consultant online. Based on the literature reviewed, a neutral facial expression would most likely have a negative influence on the perceptions, judgments and behaviors of observers. We can expect that a neutral facial expression would most likely evoke avoidance tendencies, abate approach tendencies and simultaneously decrease the likelihood to contact. Therefore, the second assumption of this study is: A2: A profile image with a neutral facial expression will decrease the tendency of the user’s likelihood to contact small B2B consultant online. 2.2. Absence of facial image Previous studies demonstrate that there is a presence effect of facial images in different online contexts (Cyr et al., 2009; Fagerstrøm et al., 2017). One of the major themes has been to examine the influence of embedding social cues, like facial images, on the trustworthiness of websites and web content. Research on online credibility has shown that author photographs had significant effects on the perceived trustworthiness of web articles (Fogg et al., 2001). Steinbrück et al. (2002) found that by including the image of customer service agents on an e-bank’s website significantly increased perceived trustworthiness. Aldiri et al. (2008) found a similar result, with a moderating effect of culture, in an e-commerce context. However, Riegelsberger and Sasse (2002) found mixed responses to the inclusion of human images in an e-commerce context. The responses varied from positive enthusiasm to negative reactions that arouse suspicion and lowered trust. Therefore, the influence of human images on perceived trustworthiness were highly dependent on the type of user. In another study, Riegelsberger et al. (2003) found that the mere presence of a human image did not have a significant effect on the trustworthiness of a website. While these studies are focused mainly on perceived trustworthiness of websites, for our study, we can confirm that there is some cognitive and/or affective impact on the perceiver of the facial images. These studies imply that the influences of mere presence effects of human facial images are highly context-specific and dependent on the users involved in the online interaction/transaction. This effect also seems to be dependent on interactions between the type of human image and the website (Riegelsberger et al., 2003). Based on this, we can infer that the absence of facial images would most likely evoke avoidance and abate approach tendencies and simultaneously decrease the tendency to contact the consultant. Therefore, the third assumption of this study, related to the lack of human facial image is: A3: The absence of social cues (human images) will decrease the tendency of the user’s likelihood to contact small B2B consultant online. 3. METHOD To test the assumptions, a conjoint analysis was used to examine how a consultant’s profile image and its facial expressions influence the approach and avoidance behavior of small B2B customers. Green and Srinivasan (1978) define conjoint analysis as a decompositional method for understanding how consumers build preferences for products or services. The term ‘conjoint’ refers to the measurement of relative values of attributes considered jointly that might be immeasurable if they were evaluated individually (Jensen, 2008). To enhance ecological validity, two additional independent variables were included in the study: educational attainment and professional experience. 3.1. Participants A population of both existing and potential B2B customer leads participated in an online survey. Six cases were removed due to missing data and one case was removed due to invalid cases, resulting in a final sample of 67 respondents. The survey was distributed internally in an international company located in Norway. This company also allowed us to access their customer database (containing previous, existing and potential leads). These participants were contacted and recruited through LinkedIn.com, a professional social networking website. Known leads were contacted directly through the premium mail service on LinkedIn. Additionally, a LinkedIn ad campaign also ran from 31 May until 1 June to recruit additional participants. All respondents were professionals with a minimum of a bachelor’s degree. The geographical distribution of the participants was 35 from Norway and 32 outside Norway representing Bermuda, Denmark, India, Italy, Nigeria, Philippines, Poland, Sweden, United Arab Emirates, the United Kingdom, and the United States. The distribution by gender was 49 men and 18 women. The age distribution was as follows: 3 participants were in the age category 18–24, 22 were in the age category 25–34, 17 were in the age category 35–44, 11 were in age category 45–54, 11 were in the age category 55–64, and, 3 were in the age category 65–74. 3.2. Apparatus The questions were hosted on limeservice.com, a web-based survey platform that is used for preparing and running online surveys. A few modifications on the interface of each slide were implemented using Cascading Style Sheets (CSS). All nine stimuli cards and other visual elements used in the survey were designed or modified using Adobe Photoshop CC 2015. All profile images are in black and white and signify a business intelligence consultant representative. The human images used for the study were taken from the comprehensive database for facial expression analysis (Kanade et al., 2000; Lucey et al., 2010), these are included in Appendix C. The facial expression images were operationalized as follows: positive facial expression was represented by a ‘smile’ image, absence of facial image was represented by ‘silhouette image’, and a neutral facial expression was represented by a ‘neutral’ image. The facial expression images (depicting ‘smile’ and ‘neutral’ expressions) were of the same individual (a Caucasian male under the age of 40). By keeping the individual in the images constant, possible confounding influences like facial attractiveness, age or ethnicity were eliminated. A few modifications were applied to the clothing on the profile images fit the given business scenario of the survey. The instructions presented in the survey were accompanied by visual aids to make them more comprehendible. An example of the stimulus cards and question is presented in Appendix A. 3.3. Procedure After the participants voluntarily accepted to take part in the study, they were presented with the following scenario: ‘You are looking for a business intelligence solution for your company, and you came across a website that offers such services. To make an inquiry, you have to send their consultant an email.’ Based on the information, the participants were presented with nine different situations that they were told to evaluate. To address our concern regarding response rate, we reduced the amount and complexity of information presented to the participant. Accordingly, a general scenario was used as to include responses from a variety of professionals from different backgrounds. Based on the given scenario, the participants were asked to answer each of the survey questions by giving it a rating of 1–10, 1 being not at all likely to contact the consultant representative and 10 being certainly would contact the consultant. The formulated questions signify the user’s desire to approach or avoid engaging with the consultant based on the combination of attributes presented in each slide. 3.4. Design Based on the participants’ evaluation of a set of complex stimuli (e.g. profile images, educational attainment and professional experience), conjoint analysis decomposes the original evaluation into separate and compatible impact scales by which the original overall evaluation can be reconstructed (Green and Wind, 1975). A fractional factorial design was used to reduce the number of stimulus cards. A fractional factorial design is a method of selecting a segment of the generated stimuli cards from a full factorial design (Hair et al., 2014). To create a realistic setting for the evaluation, a webpage was designed to mimic common website contact forms. Three website attributes that were considered for the survey were: facial expressions, educational attainment and professional experience. These attributes were chosen as a solution to compensate for the opaque quality (Von Nordenflycht, 2010) of service provider firms as they can embody the appearance and reputation of a consultant in a company. The ‘facial expression’ and ‘educational attainment’ stimuli were operationalized at three levels, and ‘professional experience’ was operationalized at two levels as presented in Table 1. IBM SPSS Statistics 24 was used to create combinations for the stimulus cards ending up with nine stimulus cards, summarized in Appendix B. TABLE 1 Antecedent stimuli and levels considered in the study. Antecedent stimuli Levels Facial expressiona Positive facial expression Absence of facial image Neutral facial expression Professional experience Senior level consultant Junior level consultant Educational attainment PhD degree Master’s degree Bachelor’s degree Antecedent stimuli Levels Facial expressiona Positive facial expression Absence of facial image Neutral facial expression Professional experience Senior level consultant Junior level consultant Educational attainment PhD degree Master’s degree Bachelor’s degree aThe two facial expression images are taken from a Cohn-Kanade AU-coded facial expression database (Kanade et al., 2000; Lucey et al., 2010) with consent for publication (see Appendix C). TABLE 1 Antecedent stimuli and levels considered in the study. Antecedent stimuli Levels Facial expressiona Positive facial expression Absence of facial image Neutral facial expression Professional experience Senior level consultant Junior level consultant Educational attainment PhD degree Master’s degree Bachelor’s degree Antecedent stimuli Levels Facial expressiona Positive facial expression Absence of facial image Neutral facial expression Professional experience Senior level consultant Junior level consultant Educational attainment PhD degree Master’s degree Bachelor’s degree aThe two facial expression images are taken from a Cohn-Kanade AU-coded facial expression database (Kanade et al., 2000; Lucey et al., 2010) with consent for publication (see Appendix C). The dependent variable was likelihood to contact the consultant. The formulated question, i.e. likelihood to contact the consultant on a scale of 1–10, would signify the user’s desire to approach or avoid engaging with the consultant (contingent on the combination of attributes presented in each slide). Based on communication-related approach-avoidance behaviors exemplified by Donovan and Rossiter (1982), higher likelihood to contact values would signify approach tendencies (i.e. a desire or willingness to communicate with others in the environment) and lower likelihood to contact values would thus signify avoidance (tendency to avoid interacting with others in the environment). The survey consisted of nine stimulus cards with different combinations of the antecedent stimuli. Participants were required to answer each survey question (one per stimulus card) before proceeding to the next slide. The task of answering the survey took the participants ~5–10 min to complete. A progress bar was displayed above the questions to notify the users of how many stimulus cards there were left in the survey. 3.5. Analysis When analyzing the data, a discrete effect was used for all three stimuli, which means that no assumption was made about the relationship between the levels and the data. IBM SPSS performs conjoint analysis using ordinary last squares. 4. RESULTS The analysis of data shows correlations between the observed preferences from the survey and estimated preferences for likelihood to contact the consultant based on the conjoint analysis (Pearson’s r = 0.994, P = 0.000). Table 2 displays the importance values for facial expression, educational attainment and professional experience and the impact estimate for each level. Evidently, in this context, human facial image was the most important antecedent stimulus with an averaged importance score of 46.938% of likelihood to contact the consultant. Educational attainment was the second most important variable, receiving an average importance score of 33.660%. The third most important stimulus was professional experience with an averaged importance score of 19.402% related to likelihood to contact the consultant. TABLE 2 Test of the impact of antecedent stimuli on likelihood to contact the consultant on a B2B website. Conjoint impact estimate and relative importance Antecedent stimuli and levels Impact estimate Importance values Standard error Facial expressions 46.938%  Positive facial expression 1.156 0.100  Absence of facial image −0.998 0.100  Neutral facial expression −0.158 0.100 Professional experience 19.402%  Senior level consultant 0.428 0.075  Junior level consultant −0.428 0.075 Educational attainment 33.660%  PhD degree 0.658 0.100  Master’s degree 0.036 0.100  Bachelor’s degree −0.695 0.100  (Constant) 4.846 0.075 Conjoint impact estimate and relative importance Antecedent stimuli and levels Impact estimate Importance values Standard error Facial expressions 46.938%  Positive facial expression 1.156 0.100  Absence of facial image −0.998 0.100  Neutral facial expression −0.158 0.100 Professional experience 19.402%  Senior level consultant 0.428 0.075  Junior level consultant −0.428 0.075 Educational attainment 33.660%  PhD degree 0.658 0.100  Master’s degree 0.036 0.100  Bachelor’s degree −0.695 0.100  (Constant) 4.846 0.075 TABLE 2 Test of the impact of antecedent stimuli on likelihood to contact the consultant on a B2B website. Conjoint impact estimate and relative importance Antecedent stimuli and levels Impact estimate Importance values Standard error Facial expressions 46.938%  Positive facial expression 1.156 0.100  Absence of facial image −0.998 0.100  Neutral facial expression −0.158 0.100 Professional experience 19.402%  Senior level consultant 0.428 0.075  Junior level consultant −0.428 0.075 Educational attainment 33.660%  PhD degree 0.658 0.100  Master’s degree 0.036 0.100  Bachelor’s degree −0.695 0.100  (Constant) 4.846 0.075 Conjoint impact estimate and relative importance Antecedent stimuli and levels Impact estimate Importance values Standard error Facial expressions 46.938%  Positive facial expression 1.156 0.100  Absence of facial image −0.998 0.100  Neutral facial expression −0.158 0.100 Professional experience 19.402%  Senior level consultant 0.428 0.075  Junior level consultant −0.428 0.075 Educational attainment 33.660%  PhD degree 0.658 0.100  Master’s degree 0.036 0.100  Bachelor’s degree −0.695 0.100  (Constant) 4.846 0.075 Table 2 shows that a consultant’s image with a smiling facial expression increases the likelihood to contact the consultant with an impact estimate score of 1.156. A consultant’s image with a neutral facial expression produced a negative score (−0.158) toward likelihood to contact the consultant. The absence of facial image (head silhouette) produced a greater negative score of −0.998 resulting in the lowest likelihood to contact the consultant (in this context). For the stimulus of educational attainment, a PhD level of education increases the likelihood to contact the consultant with an impact estimate score of 0.658. A master’s level of education produced an impact estimate score of 0.036. The bachelor’s level of education received the lowest average impact score of −0.695. The professional experience stimulus received the lowest importance value score, which is reflected in the impact estimate scores. Results from the survey show that respondents favored the senior level consultant over the junior level, with an impact score of 0.428 for senior level and −0.428 for the junior level consultant. The data indicate a higher possibility for likelihood to contact for a senior level consultant than for a junior level consultant. A scenario simulation was devised where facial expression levels varied in relation to top and bottom scenarios on education and experience. All cases (A–F) were analyzed in relation to each other. Table 3 above shows the stimuli and levels for each of the cases. The outcomes for each case are shown according to preference scores along with three preference probability scores: Maximum utility, Bradley–Terry–Luce (BTL) and Logit. Maximum utility probability is the primary method to analyze the results, as engaging a consultant is a sporadic rather than a routine activity for the participants. BTL and Logit are optimal measurements for repetitive purchase situations, while Maximum utility is suited for sporadic and non-routine purchases (Hair et al., 2014). TABLE 3 Outcomes of the scenario simulation analysis related on likelihood to contact the consultant on a B2B website. Stimuli and Levels Outcomes Scenarios Cases Facial expressions Educational attainment Professional experience Preference scores Maximum utilitya (%) Bradley–Terry–Luceb (%) Logitb (%) Top education and experience A Positive facial expression PhD degree Senior level consultant 7.088 64.2 23.2 44.2 Top education and experience B Absence of facial image PhD degree Senior level consultant 4.934 5.6 16.7 12.5 Top education and experience C Neutral facial expression PhD degree Senior level consultant 5.774 15.3 19.4 20.9 Bottom education and experience D Positive facial expression Bachelor´s degree Junior level consultant 4.879 10.4 17.0 12.9 Bottom education and experience E Absence of facial image Bachelor´s degree Junior level consultant 2.725 1.9 10.5 3.8 Bottom education and experience F Neutral facial expression Bachelor´s degree Junior level consultant 3.566 2.6 13.2 5.6 Stimuli and Levels Outcomes Scenarios Cases Facial expressions Educational attainment Professional experience Preference scores Maximum utilitya (%) Bradley–Terry–Luceb (%) Logitb (%) Top education and experience A Positive facial expression PhD degree Senior level consultant 7.088 64.2 23.2 44.2 Top education and experience B Absence of facial image PhD degree Senior level consultant 4.934 5.6 16.7 12.5 Top education and experience C Neutral facial expression PhD degree Senior level consultant 5.774 15.3 19.4 20.9 Bottom education and experience D Positive facial expression Bachelor´s degree Junior level consultant 4.879 10.4 17.0 12.9 Bottom education and experience E Absence of facial image Bachelor´s degree Junior level consultant 2.725 1.9 10.5 3.8 Bottom education and experience F Neutral facial expression Bachelor´s degree Junior level consultant 3.566 2.6 13.2 5.6 aIncluding tied simulations. b56 out of 67 subjects are used in the Bradley–Terry–Luce and Logit methods because these subjects all have non-negative scores. TABLE 3 Outcomes of the scenario simulation analysis related on likelihood to contact the consultant on a B2B website. Stimuli and Levels Outcomes Scenarios Cases Facial expressions Educational attainment Professional experience Preference scores Maximum utilitya (%) Bradley–Terry–Luceb (%) Logitb (%) Top education and experience A Positive facial expression PhD degree Senior level consultant 7.088 64.2 23.2 44.2 Top education and experience B Absence of facial image PhD degree Senior level consultant 4.934 5.6 16.7 12.5 Top education and experience C Neutral facial expression PhD degree Senior level consultant 5.774 15.3 19.4 20.9 Bottom education and experience D Positive facial expression Bachelor´s degree Junior level consultant 4.879 10.4 17.0 12.9 Bottom education and experience E Absence of facial image Bachelor´s degree Junior level consultant 2.725 1.9 10.5 3.8 Bottom education and experience F Neutral facial expression Bachelor´s degree Junior level consultant 3.566 2.6 13.2 5.6 Stimuli and Levels Outcomes Scenarios Cases Facial expressions Educational attainment Professional experience Preference scores Maximum utilitya (%) Bradley–Terry–Luceb (%) Logitb (%) Top education and experience A Positive facial expression PhD degree Senior level consultant 7.088 64.2 23.2 44.2 Top education and experience B Absence of facial image PhD degree Senior level consultant 4.934 5.6 16.7 12.5 Top education and experience C Neutral facial expression PhD degree Senior level consultant 5.774 15.3 19.4 20.9 Bottom education and experience D Positive facial expression Bachelor´s degree Junior level consultant 4.879 10.4 17.0 12.9 Bottom education and experience E Absence of facial image Bachelor´s degree Junior level consultant 2.725 1.9 10.5 3.8 Bottom education and experience F Neutral facial expression Bachelor´s degree Junior level consultant 3.566 2.6 13.2 5.6 aIncluding tied simulations. b56 out of 67 subjects are used in the Bradley–Terry–Luce and Logit methods because these subjects all have non-negative scores. According to Maximum utility probability, as viewed in Table 3, the top case is case A, where 64.2% of the participants prefer a senior level consultant, with a PhD education, and, a positive facial expression, over cases B to F. Scenario C is second most preferred, where 15.3% of the participants prefer a senior level consultant, with a PhD education, and, a neutral facial expression. Third preferred scenario is scenario D, where 10.4% of the participants preferred a junior level consultant with a Bachelor’s degree, and, a positive facial expression. The least preferred scenarios are B, F and E with a maximum utility score of 5.6, 2.6 and 1.9%, respectively. 5. DISCUSSION This empirical research investigated how human facial images, with a focus on facial expressions (smiling and neutral) affect a user’s likelihood to contact B2B consultants online. This research contributes to the literature by demonstrating the relative importance of different web elements in the context of B2B consultation websites. The facial image of the consultant on the B2B consultation website was the most important antecedent stimuli, followed by educational attainment. Professional experience was the least influential stimuli in this specific context. To recap, the specific assumptions made for this study were as follows: A1: A profile image with a positive facial expression will increase the tendency of the user’s likelihood to contact the small B2B consultant online. A2: A profile image with a neutral facial expression will decrease the tendency of the user’s likelihood to contact small B2B consultant online. A3: The absence of social cues (human images) will decrease the tendency of the user’s likelihood to contact small B2B consultant online. The results from the present study demonstrate that a consultant’s image with a smiling facial expression increases the likelihood to contact the consultant, therefore, A1 was supported. This indicates that on a consultation services website, B2B customers were influenced mostly by the ‘non-functional’ element, that is, facial expression. For the smiling facial image, the consultant might have been judged favorably (Otta et al., 1994), which is in line with research that demonstrates how a smiling expression positively influences the perception of social characteristics (Hess et al., 2000; Knutson, 1996; Scharlemann et al., 2001). The results support recent studies that show that smiles have a positive impact, even in online settings (Cyr et al., 2009; Fagerstrøm et al., 2017). However, another possible reason for this result could be that the nature of the task is not highly risky. The scenario only requires the customers to inquire, not to recruit. It is possible that the customers would have taken the task of reviewing the collective information more seriously (educational attainment and professional experience) if they were actually asked to consider purchasing the services of the consultancy. Compared to the smiling picture of the consultant, the face with a neutral expression resulted in a lesser likelihood to be contacted by potential customers, supporting A2. The finding is consistent with studies discussed, which demonstrate that a neutral facial expression has a negative influence on perceivers in social situations (Krumhuber et al., 2007; Scharlemann et al., 2001). A possible explanation for this effect is that we used the image of a male displaying the neutral expression. This might have resulted in negative personality trait associations, i.e. dominance (Hareli et al., 2009). Compared to the other two conditions, the absence of social cues (human images) resulted in the lowest likelihood to contact the consultant, therefore, A3 was also supported. Our findings are in line with previous research showing that facial photos and social presence cues on e-commerce websites can have positive influences on users (Aldiri et al., 2008; Cyr et al., 2009; Fogg et al., 2001; Steinbrück et al., 2002). Hence, the absence of facial images could have caused the environment to feel more artificial and less social. These factors might have produced a reduction in the likelihood to contact tendency in potential B2B customers. The scenario simulation analysis shows that facial expressions are influential factors in this B2B context. The findings demonstrated that for the antecedent stimuli neutral facial expression and absence of facial image resulted reduced preference probabilities (when compared to positive facial expression). It is evident that these antecedent stimuli cannot be compensated for by high educational level and professional experience. The findings from this study complement previous literature that examines the influence of facial expressions in profile images (Fagerstrøm et al., 2017) in consumer contexts. We extend this finding by taking this research into a B2B context and showing that facial expressions do have an impact in more formal, corporate settings. 5.1. Practical implications This article contributes to the existing body of knowledge on the impact of human facial images on the behavior of users online. The study presents several practical implications for web designers, consultants and B2B companies that provide services. Findings from this investigation reveal that using human images with varying facial expressions on B2B websites can influence the behavior of users in either a positive or a negative way. It would, therefore, be advisable for web designers and content creators to test and incorporate human faces in B2B websites (Fogg et al., 2001) and consider the use of a smiling expression (especially an authentic smile) as it creates a more inviting web environment. This can potentially lead to higher conversion rates or increase the tendency of a customer to initiate contact. These types of minor website changes could especially help small B2B businesses with limited resources to develop their online presence. For B2B companies that capitalize on selling services, the assessment of quality has been one of the main marketing issues (Virtsonis and Harridge-March, 2008; Von Nordenflycht, 2010). This study emphasizes the importance of the consultant’s image and facial expression in creating a positive first impression which might influence the client’s behaviors. It would be advisable to select senior consultants with a high level of education or provide more information on the consultant’s professional experience. These factors can be potential indicators of the quality of services that a B2B firm can provide. 5.2. Limitations and future research Due to the broadness of the topics covered in this study, certain aspects of the research call for further investigation. The direction for future research could involve the enhancement of the survey design as well as the improvement of the conceptual framework used in this study. Future research could employ the full set of approach-avoidance questions to measure actual approach-avoidance tendencies behavior (Russell and Mehrabian, 1978). The method of conducting the online-based survey was a success. However, there are some limitations in terms of monitoring the participants in the way that they answer the survey. During data collection, more than 50 incomplete samples were discarded from the study, most were repeated attempts from the respondents due to slow Internet connections or due to misinterpretation of instructions. In this study, the list of antecedent stimuli used were presented sequentially, causing order effects (Chrzan, 1994). A follow-up study could be done to arrange the conjoint study in a controlled experimental setting, thereby controlling for order effects by randomized presentation of the stimulus cards. The sample population consisted of 67 B2B customers. The analysis gave significant values and low estimate of standard error, resulting in a strong statistical conclusion validity (Table 2). Despite the small sample size, it should be highlighted that the sample size consisted of actual organizational decision-makers from the industry. Sample sizes vary considerably in studies that employ conjoint analysis (Naous and Legner, 2017; Wittink et al., 1994). The conjoint experiment retains its statistical significance despite a smaller sample size. External validity might be low due to the homogeneity of participants, the artificial scenario situation, and the relatively smaller sample size. It would be interesting to replicate the study with more B2B customers with different cultural backgrounds. This would verify the results of the present study and, in addition, cultural differences can be analyzed (Aldiri et al., 2008). In our stimulus images, we used a grayscale profile image of a relatively younger looking male consultant. Future experiments could use color images of male and female consultants displaying the same expressions (see Cardon et al., 2018; Tifferet and Vilnai-Yavetz, 2018 for gender differences in profile images on professional websites). Facial attractiveness is another aspect that has been shown to have a significant impact in a variety of corporate human interactions (Hosoda et al., 2003), and even interactions with embodied communication agents (Yuksel et al., 2017). Research on embodied agents covers many aspects of nonverbal behavior, including facial expressions (Bickmore and Cassell, 2005; Cassell et al., 1994, 1999). Since embodied agents are being used for a variety of different contexts, theoretically, they could be used to cover the same initial stages of B2B communication as covered in this study. It would be very interesting for future researchers to examine such topics further. The level of experience and degree level of the consultant could also be examined further, as some may contend that the consultant’s prior work experiences, statement from previous clients, and especially certifications, could also serve as benchmarks for prospective clientele (Gross and Poor, 2008). Additionally, the impact of the attributes examined could be studied in conjunction with and independent of price. B2B services/products, on average, are often considerably more expensive compared to B2C offerings, and this is one of the main reasons that decision-making is considered as more complex and involves many people. In this study, there is no information about the consultation charges. There could be significantly different results if the participants are given an indication of consultation charges. A higher price could mean more risk, which could alter the importance of the other attributes examined in this study. Future studies could use a more detailed decision-making scenario and compare the results with this study to see how a more risky scenario would influence the relative impact of the three antecedent variables used in this study. 6. CONCLUSION The study demonstrated how small improvements on a website such as adding social cues like human profile images could significantly influence the behavior of website visitors. Through a method of conjoint analysis, this study investigated the impact of three attributes of human face images—positive facial expression, neutral facial expression, and absence of facial image—on the behavior of B2B website visitors. A collection of literature in the topic of B2B marketing strategy, human face perception and conjoint analysis was studied to find and develop links between the concepts used in the study. A total of 67 professionals, both existing and prospective B2B customers participated in the web-based survey. Results from the study revealed the importance of human facial images and inherent expressions in online contexts. From the three stimuli selected for the study, the human face image stimulus was revealed to be the most important variable, followed by the educational attainment and professional experience. As anticipated, the image of a consultant depicting a smiling facial expression elicited the most likelihood of contact from respondents, followed by the neutral facial expression. The absence of a facial image had the least impact in this context. Since there is not much literature covering this topic, especially within the context of B2B websites, there is an opportunity for significant future contributions to both management practice and academia. REFERENCES Aldiri , K. , Hobbs , D. and Qahwaji , R. ( 2008 ) The human face of e-business: engendering consumer initial trust through the use of images of sales personnel on e-commerce web sites . Int. J. E-Bus. Res. , 4 , 58 . Google Scholar Crossref Search ADS Baker , J. , Grewal , D. and Parasuraman , A. ( 1994 ) The influence of store environment on quality inferences and store image . J. Acad. Mark. Sci. , 22 , 328 – 339 . Google Scholar Crossref Search ADS Bickmore , T. and Cassell , J. ( 2005 ) Social dialongue with embodied conversational agents. In Advances in Natural Multimodal Dialogue Systems . pp. 23 – 54 . Springer . Bitner , M.J. ( 1992 ) Servicescapes: the impact of physical surroundings on customers and employees . J. Mark. , 56 , 57 – 71 . Google Scholar Crossref Search ADS Cardon , P. , Li , H. and Shi , H. ( 2018 ) Displays of status and expressiveness in professional profile pictures on LinkedIn and corporate websites: a cross-cultural comparison of China and the United States . Glob. Adv. Bus. Commun. , 7 , 4 . Cassell , J. , Bickmore , T. , Billinghurst , M. , et al. ( 1999 ) Embodiment in conversational interfaces: Rea. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems. Cassell , J. , Pelachaud , C. , Badler , N. , et al. ( 1994 ) Animated conversation: rule-based generation of facial expression, gesture & spoken intonation for multiple conversational agents. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques. Chrzan , K. ( 1994 ) Three kinds of order effects in choice-based conjoint analysis . Mark. Lett. , 5 , 165 – 172 . doi:10.1007/BF00994106 . Google Scholar Crossref Search ADS Clark , W.R. , Ezell , J. , Clark , J. and Sheffield , D.N. ( 2009 ) Stay or leave: applying approach–avoidance theory to virtual environments . J. Database Mark. Customer Strategy Manage. , 16 , 231 – 240 . Google Scholar Crossref Search ADS Crivelli , C. and Fridlund , A.J. ( 2018 ) Facial displays are tools for social influence . Trends Cogn. Sci. , 22 , 388 – 399 . Google Scholar Crossref Search ADS PubMed Crivelli , C. , Jarillo , S. , Russell , J.A. and Fernández-Dols , J.-M. ( 2016 a) Reading emotions from faces in two indigenous societies . J. Exp. Psychol. Gen. , 145 , 830 . Google Scholar Crossref Search ADS PubMed Crivelli , C. , Russell , J.A. , Jarillo , S. and Fernández-Dols , J.-M. ( 2016 b) The fear gasping face as a threat display in a Melanesian society . Proc. Natl. Acad. Sci. , 113 , 12403 – 12407 . Google Scholar Crossref Search ADS Crivelli , C. , Russell , J.A. , Jarillo , S. and Fernández-Dols , J.-M. ( 2017 ) Recognizing spontaneous facial expressions of emotion in a small-scale society of Papua New Guinea . Emotion , 17 , 337 . Google Scholar Crossref Search ADS PubMed Cyr , D. , Head , M. , Larios , H. and Pan , B. ( 2009 ) Exploring human images in website design: a multi-method approach . MIS Quart. , 33 , 539 – 566 . Google Scholar Crossref Search ADS Donovan , R. and Rossiter , J. ( 1982 ) Store atmosphere: an environmental psychology approach . J. Retailing , 58 , 34 – 57 . Donovan , R.J. , Rossiter , J.R. , Marcoolyn , G. and Nesdale , A. ( 1994 ) Store atmosphere and purchasing behavior . J. Retailing , 70 , 283 – 294 . Google Scholar Crossref Search ADS Ekman , P. ( 1994 ) Strong evidence for universals in facial expressions: a reply to Russell’s mistaken critique. Psychol. Bull. , 115, 268 – 287 . Ekman , P. and Friesen , W.V. ( 1971 ) Constants across cultures in the face and emotion . J. Pers. Soc. Psychol. , 17 , 124 . Google Scholar Crossref Search ADS PubMed Elfenbein , H.A. and Ambady , N. ( 2002 ) On the universality and cultural specificity of emotion recognition: a meta-analysis . Psychol. Bull. , 128 , 203 . Google Scholar Crossref Search ADS PubMed Eroglu , S.A. , Machleit , K.A. and Davis , L.M. ( 2001 ) Atmospheric qualities of online retailing: a conceptual model and implications . J. Bus. Res. , 54 , 177 – 184 . Google Scholar Crossref Search ADS Eroglu , S.A. , Machleit , K.A. and Davis , L.M. ( 2003 ) Empirical testing of a model of online store atmospherics and shopper responses . Psychol. Mark. , 20 , 139 – 150 . Google Scholar Crossref Search ADS Fagerstrøm , A. , Pawar , S. , Sigurdsson , V. , Foxall , G.R. and Yani-de-Soriano , M. ( 2017 ) That personal profile image might jeopardize your rental opportunity! On the relative impact of the seller’s facial expressions upon buying behavior on Airbnb™ . Comput. Hum. Behav. , 72 , 123 – 131 . Google Scholar Crossref Search ADS Fill , C. ( 2005 ) Marketing Communications: Engagements, Strategies and Practice . Pearson Education . Fogg , B.J. , Marshall , J. , Kameda , T. , et al. ( 2001 ) Web credibility research: a method for online experiments and early study results. In CHI’01 Extended Abstracts on Human Factors in Computing Systems. Fridlund , A.J. ( 2014 ) Human Facial Expression: An Evolutionary View . Academic Press . Gendron , M. ( 2017 ) Revisiting diversity: cultural variation reveals the constructed nature of emotion perception . Curr. Opin. Psychol. , 17 , 145 – 150 . Google Scholar Crossref Search ADS PubMed Gendron , M. , Roberson , D. , van der Vyver , J.M. and Barrett , L.F. ( 2014 ) Perceptions of emotion from facial expressions are not culturally universal: evidence from a remote culture . Emotion , 14 , 251 . Google Scholar Crossref Search ADS PubMed Green , P.E. and Srinivasan , V. ( 1978 ) Conjoint analysis in consumer research: issues and outlook . J. Consum. Res. , 5 , 103 – 123 . Google Scholar Crossref Search ADS Green , P.E. and Wind , Y. ( 1975 ) New way to measure consumer’s judgments . Harv. Bus. Rev. , 53 , 107 – 117 . Gross , A.C. and Poor , J. ( 2008 ) The global management consulting sector . Bus. Econ. , 43 , 59 – 68 . Google Scholar Crossref Search ADS Hair , J.F. , Black , W.C. , Babin , B.J. and Anderson , R.E. ( 2014 ) Multivariate Data Analysis ( 7th edn ). Pearson Prentice Hall , Upper Saddle River New Jersey . Hareli , S. , Shomrat , N. and Hess , U. ( 2009 ) Emotional versus neutral expressions and perceptions of social dominance and submissiveness . Emotion , 9 , 378 . Google Scholar Crossref Search ADS PubMed Hess , U. , Blairy , S. and Kleck , R.E. ( 2000 ) The influence of facial emotion displays, gender, and ethnicity on judgments of dominance and affiliation . J. Nonverbal Behav. , 24 , 265 – 283 . Google Scholar Crossref Search ADS Hosoda , M. , Stone‐Romero , E.F. and Coats , G. ( 2003 ) The effects of physical attractiveness on job‐related outcomes: a meta‐analysis of experimental studies . Pers. Psychol. , 56 , 431 – 462 . Google Scholar Crossref Search ADS Izard , C.E. ( 1994 ) Innate and universal facial expressions: evidence from developmental and cross-cultural research. Psychol. Bull. , 115, 288 – 299 . Izard , C.E. ( 1997 ) Emotions and facial expressions: a perspective from Differential Emotions Theory . Psychol. Fac. Expr. , 2 , 57 – 77 . Jack , R.E. , Blais , C. , Scheepers , C. , Schyns , P.G. and Caldara , R. ( 2009 ) Cultural confusions show that facial expressions are not universal . Curr. Biol. , 19 , 1543 – 1548 . Google Scholar Crossref Search ADS PubMed Jack , R.E. , Garrod , O.G.B. , Yu , H. , Caldara , R. and Schyns , P.G. ( 2012 ) Facial expressions of emotion are not culturally universal . Proc. Natl. Acad. Sci. , 109 , 7241 – 7244 . Google Scholar Crossref Search ADS Jensen , M.B. ( 2008 ) Planning of online and offline B2B promotion with conjoint analysis . J. Target. Meas. Anal. Mark. , 16 , 203 – 213 . Google Scholar Crossref Search ADS Kanade , T. , Cohn , J.C. and Tian , Y. ( 2000 ) Comprehensive database for facial expression analysis. Automatic Face and Gesture Recognition, 2000. In Proceedings. Fourth IEEE International Conference on, Grenoble, France. Knutson , B. ( 1996 ) Facial expressions of emotion influence interpersonal trait inferences . J. Nonverbal Behav. , 20 , 165 – 182 . Google Scholar Crossref Search ADS Kotler , P. and Pfoertsch , W. ( 2006 ) B2B Brand Management . Springer Science & Business Media . Krumhuber , E. , Manstead , A.S.R. , Cosker , D. , Marshall , D. , Rosin , P.L. and Kappas , A. ( 2007 ) Facial dynamics as indicators of trustworthiness and cooperative behavior . Emotion , 7 , 730 . Google Scholar Crossref Search ADS PubMed LaFrance , M. and Hecht , M.A. ( 1995 ) Why smiles generate leniency . Pers. Soc. Psychol. Bull. , 21 , 207 – 214 . Google Scholar Crossref Search ADS Lucey , P. , Cohn , J.F. , Kanade , T. , Saragih , J. , Ambadar , Z. and Matthews , I. ( 2010 ) The extended cohn-kanade dataset (ck+): a complete dataset for action unit and emotion-specified expression. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on, San Francisco, USA. Lynch , J. and De Chernatony , L. ( 2004 ) The power of emotion: brand communication in business-to-business markets . J. Brand Manage. , 11 , 403 – 419 . Google Scholar Crossref Search ADS Marsh , A.A. , Ambady , N. and Kleck , R.E. ( 2005 ) The effects of fear and anger facial expressions on approach-and avoidance-related behaviors . Emotion , 5 , 119 . Google Scholar Crossref Search ADS PubMed Mehrabian , A. and Russell , J.A. ( 1974 ) An Approach to Environmental Psychology . The MIT Press . Mussel , P. , Göritz , A.S. and Hewig , J. ( 2013 ) The value of a smile: facial expression affects ultimatum-game responses . Judgm. Decis. Mak. , 8 , 381 . Naous , D. and Legner , C. ( 2017 ) Leveraging Market Research Techniques in IS – A Review of Conjoint Analysis in IS Research. Proceedings. 8. Thirty eighth International Conference on Information Systems (ICIS), Seoul, 2017. http://aisel.aisnet.org/icis2017/IS-Development/Presentations/8 Otta , E. , Lira , B.B.P. , Delevati , N.M. , Cesar , O.P. and Pires , C.S.G. ( 1994 ) The effect of smiling and of head tilting on person perception . J. Psychol. , 128 , 323 – 331 . Google Scholar Crossref Search ADS PubMed Riegelsberger , J. and Angela Sasse , M. ( 2002 ) Face it-photos don’t make a web site trustworthy. In CHI’02 Extended Abstracts on Human Factors in Computing Systems. Riegelsberger , J. , Angela Sasse , M. and McCarthy , J.D. ( 2003 ) Shiny happy people building trust?: photos on e-commerce websites and consumer trust. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Russell , J.A. and Mehrabian , A. ( 1978 ) Approach-avoidance and affiliation as functions of the emotion-eliciting quality of an environment . Environ. Behav. , 10 , 355 – 387 . Google Scholar Crossref Search ADS Scharlemann , J.P.W. , Eckel , C.C. , Kacelnik , A. and Wilson , R.K. ( 2001 ) The value of a smile: game theory with a human face . J. Econ. Psychol. , 22 , 617 – 640 . Google Scholar Crossref Search ADS Schneider , K.G. , Hempel , R.J. and Lynch , T.R. ( 2013 ) That ‘poker face’ just might lose you the game! The impact of expressive suppression and mimicry on sensitivity to facial expressions of emotion . Emotion , 13 , 852 . Google Scholar Crossref Search ADS PubMed Snyder , K. and Hilal , P. ( 2015 ) The changing face of B2B marketing. Think With Google. https://www.thinkwithgoogle.com/consumer-insights/the-changing-face-b2b-marketing/. Solomon , M.R. ( 2009 ) Marketing: Real People, Real Decisions . Pearson Education . Steinbrück , U. , Schaumburg , H. , Duda , S. and Krüger , T. ( 2002 ) A picture says more than a thousand words: photographs as trust builders in e-commerce websites. In CHI’02 Extended Abstracts on Human Factors in Computing Systems. Stins , J.F. , Roelofs , K. , Villan , J. , Kooijman , K. , Hagenaars , M.A. and Beek , P.J. ( 2011 ) Walk to me when I smile, step back when I’m angry: emotional faces modulate whole-body approach–avoidance behaviors . Exp. Brain Res. , 212 , 603 – 611 . Google Scholar Crossref Search ADS PubMed Tifferet , S. and Vilnai-Yavetz , I. ( 2018 ) Self-presentation in LinkedIn portraits: common features, gender, and occupational differences . Comput. Hum. Behav. , 80 , 33 – 48 . Google Scholar Crossref Search ADS Van Dijck , J. ( 2013 ) ‘You have one identity’: performing the self on Facebook and LinkedIn . Media Cult. Soc. , 35 , 199 – 215 . Google Scholar Crossref Search ADS Virtsonis , N. and Harridge-March , S. ( 2008 ) Website elements in B2B online communications: a case from the UK print industry . Mark. Intell. Plann. , 26 , 699 – 718 . Google Scholar Crossref Search ADS Von Nordenflycht , A. ( 2010 ) What is a professional service firm? Toward a theory and taxonomy of knowledge-intensive firms . Acad. Manage. Rev. , 35 , 155 – 174 . Wittink , D.R. , Vriens , M. and Burhenne , W. ( 1994 ) Commercial use of conjoint analysis in Europe: results and critical reflections . Int. J. Res. Mark. , 11 , 41 – 52 . Google Scholar Crossref Search ADS Yuksel , B.F. , Collisson , P. and Czerwinski , M. ( 2017 ) Brains or beauty: how to engender trust in user-agent interactions . ACM Trans. Internet Technol. , 17 , 2 . Google Scholar Crossref Search ADS Appendix Appendix A An example of a stimulus card used in the study. View largeDownload slide View largeDownload slide Appendix B Factorial design used to synthesize stimulus cards. Stimuli and levels Stimulus card Facial expression Professional experience Educational attainment 1 3 1 3 2 1 1 2 3 3 1 1 4 1 2 3 5 2 1 3 6 3 2 2 7 2 1 2 8 2 2 1 9 1 1 1 Stimuli and levels Stimulus card Facial expression Professional experience Educational attainment 1 3 1 3 2 1 1 2 3 3 1 1 4 1 2 3 5 2 1 3 6 3 2 2 7 2 1 2 8 2 2 1 9 1 1 1 Note. Antecedent stimuli and their levels correspond to Table 1. View Large Factorial design used to synthesize stimulus cards. Stimuli and levels Stimulus card Facial expression Professional experience Educational attainment 1 3 1 3 2 1 1 2 3 3 1 1 4 1 2 3 5 2 1 3 6 3 2 2 7 2 1 2 8 2 2 1 9 1 1 1 Stimuli and levels Stimulus card Facial expression Professional experience Educational attainment 1 3 1 3 2 1 1 2 3 3 1 1 4 1 2 3 5 2 1 3 6 3 2 2 7 2 1 2 8 2 2 1 9 1 1 1 Note. Antecedent stimuli and their levels correspond to Table 1. View Large Appendix C The two facial expression images (‘joy’ and ‘neutral’) are taken from Cohn-Kanade AU-coded facial expression database (©Jeffrey Cohn) with consent for publication (Kanade et al., 2000; Lucey et al., 2010). View largeDownload slide View largeDownload slide Author notes Editorial Board Member: Timothy Bickmore © The Author(s) 2019. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Examining the Relative Impact of Professional Profile Images and Facial Expressions in Small Business-to-Business Marketing Online
JF - Interacting with Computers
DO - 10.1093/iwc/iwz005
DA - 2019-01-01
UR - https://www.deepdyve.com/lp/oxford-university-press/examining-the-relative-impact-of-professional-profile-images-and-cMBDqA0Cus
SP - 83
VL - 31
IS - 1
DP - DeepDyve
ER -