# How social media use enhances salesperson performance

Romain Franck, Maud Damperat

► To cite this version:

Romain Franck, Maud Damperat. How social media use enhances salesperson performance. Journal of Business and Industrial Marketing, 2023, 38 (8), pp.1720-1737. 10.1108/JBIM-02-2022-0082. halshs-04159471

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# How Social Media Use Enhances Salesperson Performance

## Abstract:

**Purpose:** Based on a relationship marketing approach, this paper studies the influence of social media use on salesperson performance and its underlying mechanisms from the perspective of salespeople in B2B settings.

**Design/methodology/approach:** To test the proposed model, we used structural equation modeling with a sample of 196 French B2B salespeople. Moreover, to explore the moderating effect of emotional management between social media use and relationship quality, we used the Hayes macro PROCESS for SPSS and the Johnson-Newman's floodlight method.

**Findings:** We confirm the direct role of social media use on salesperson performance, and its indirect role through the parallel mediation of social proximity and relationship quality. Our empirical study provides evidence for the moderating effect of emotional management on the relationship between social media use and relationship quality.

**Originality:** The research complements the conceptualization of salesperson performance as a combination of sales performance and sales creativity, and shows that emotional management is an asset for social media users to develop valuable business relationships.

**Practical implications:** Companies should promote the use of social media to increase both the sales and creative performance of salespeople. Moreover, salespeople with low to moderate abilities to manage other people's emotions benefit strongly from the use of social media, as this directly increases their relationship with their customers.

**Keywords:** B2B sales, Relationship marketing, Relationship quality, Salesperson performance, Social media use, Social proximity.
# How Social Media Use Enhances Salesperson Performance

## Introduction

Buyers are changing their preferences from face-to-face to virtual relationships, leading to a future full of opportunities for salespeople using social media (Chaker et al., 2022). Three out of four B2B buyers use social media to engage in the buying process and make final purchase decisions (Minsky and Quesenberry, 2016). The way of selling in B2B is evolving: salespeople can meet prospects, make offers, and ensure that customers follow updates through social media. By becoming aware of customers' views early on, salespeople increase their chances of winning business (Ancillai et al., 2019). Thus, a strategic question for marketing and sales departments is whether they should promote the use of social media by salespeople, which involves investing in these technologies and in training (Julienne et al., 2019). With the development of social media, salespeople are constantly connected to their customers and managers (Marshall et al., 2012). Being active on social media allows salespeople to be present earlier in the buyer's trajectory, thereby giving them a better chance of participating in the development of business solutions for customers. Yet while some salespeople appreciate the use of social media, others display reluctance on the grounds that only face-to-face meetings are able to create long-lasting relationships. Indeed, salespeople may not be able to take full advantage of the usefulness of social media if they simply use them without understanding their importance (Tiwary et al., 2021). This lack of a common viewpoint may be due to the fact that empirical research on social media use is extremely limited (Agnihotri et al., 2016), and the nature of social media use needs to be broken down in order to examine its effects on social capital creation and appropriation (Agnihotri, 2021). Thus, we propose to examine the influence of social media use on salesperson performance and its underlying relational mechanisms.

Various theoretical approaches, mainly information and communication based, have been deployed to understand the influence of social media use. Some studies show that social media can be used for gathering information to acquire a better understanding of customers (Lacoste, 2016), build a network, and interact with stakeholders (Bocconcelli et al., 2017; Lacoste, 2016). According to Andzulis et al. (2012), networks on social media can be used to build awareness and gain referrals, and active use of social media can help salespeople
improve their communication with customers. Other studies note that salespeople try to
enhance their reputation by joining communities, sharing posts or blogging (Lacoste, 2016;
Rollins et al., 2014), and by exerting social influence in online communities (Wang et al.,
2016). Bowen et al. (2021) argue that by giving B2B salespersons an opportunity to
communicate directly with their customers, social media are used by salespeople to provide a
proactive service to their customers, and hence can play a critical role in driving sales
performance. Yet the relational mechanisms through which the use of social media influence
salespeople's performance remain unclear for practitioners. Indeed, B2B sales managers and
salespeople are uncertain, or even skeptical, about possible enhanced performance stemming
from social media use by salespeople (Bowen et al., 2021).

Few studies focus on social media use from a relationship marketing standpoint.
Moreover, the role of social media use that modifies touch points and the development of the
buyer-seller relationship has been little studied. Palmatier et al. (2006) demonstrate the
mediating role played by relationship quality (i.e. satisfaction, trust, and engagement), but we
need to understand how social media relate to B2B salespeople's tasks and performance
(Bowen et al., 2021), how social technologies and applications influence the depth and
breadth of the relationship between buyers and sellers (Arli et al., 2018), how social media
selling strategies impact customer satisfaction (Kumar and Sharma, 2022), and how social
media use influences social capital creation and appropriation (Agnihotri, 2021). We thus
propose to enhance understanding of the role played by social media through social proximity
and the effect of enhanced relationship quality on salesperson performance.

The use of social media contributes to the development of relationships in B2B settings
and leads to a reconsideration by salespeople—the key players in the management of
customers relationships—of the role of emotional management. Organizational buyers are not
only be driven by logic, testing and facts, but also by their emotions (Bagozzi, 2006).
Emotions are psychological forces that can strongly influence the behavior and performance
of salespeople (Brown et al., 1997) and are inherent in the connections created by interactions
with salespeople (Singh and Venugopal, 2015). Understanding and using emotions, and
managing them satisfactorily, is particularly important for salespeople for developing long-
term relationships. The concept of emotional intelligence (EI) was introduced by Goleman
(1995), and its influence has been tested in a variety of business contexts, such as leadership,
teambuilding and sales (Kidwell et al., 2012). In B2B settings, the increasing use of social media invites researchers to study the role of salespeople's emotional intelligence on relationship management. Kemp et al. (2020) highlight the importance of emotions in decision-making and point out that marketing communication can be a potentially valuable tool for strengthening the connection between buyers and suppliers. Kemp et al. (2018) show that specific marketing messages on social media can manage, influence, and regulate emotions in the buying process, and stress the role of emotions in contributing to personal value.

Drawing on relationship marketing (Palmatier et al., 2006), we study the influence of social media use on salesperson performance in B2B settings. We also seek to understand the underlying mechanisms that might explain the influence of social media use on salesperson performance. We thus examine the mediating effect of relational mediators (i.e., social proximity and relationship quality) between social media use and salesperson performance. We also study the moderating role of salespeople's emotional management in the relationship between the use of social media and both salesperson performance and social proximity. Our research is thus in line with the work of Park et al. (2010), who study the quality of the relationship as a complementary mediator of the relationship between the use of sales support technologies, such as social media, and salespeople's performance. More specifically, we examine: (1) the nature and measurement of the salesperson's performances; (2) the underlying mechanisms that lead social media use to influence the salesperson's performance; (3) the moderating role of salesperson emotional management for building valuable quality relationships using social media tools. The originality of this paper lies in its development of the conceptualization of salesperson performance as a combination of sales performance and sales creativity, and in showing that emotional management is an asset for social media users in developing valuable business relationships.

# Literature Review

## *Social Media in B2B Sales*

A key theme that emerges from the technology literature in sales (Ahearne et al., 2004; Jelinek et al., 2006; Speier and Venkatesh, 2002) is that the use of technology within the sales
force is a necessary but not a sufficient criterion and that the manner in which salespeople use
technology determines performance outcomes (Ogilvie et al., 2018). By allowing greater
efficiency in the performance of the tasks to be accomplished, the use of technologies such as
social media by salespeople is likely to improve their performance in terms of sales (Franke
and Park, 2006; Park et al., 2010). In addition, social media offers B2B companies the
opportunity to gather valuable information from their customers, and connect and establish a
dialogue with them (Keinänen and Kuivalainen, 2015). The information that salespeople can
access through social media in particular can enable them to identify new customer needs,
find new solutions and close sales (Park et al., 2010).

Social media are associated with different technologies able to provide users with
services such as networking, online search, and analytics (O'Reilly and Battelle, 2009).
According to Kaplan and Haenlein (2010), social media comprise a group of internet-based
applications that build on the ideological and technological foundations of Web 2.0, and that
enable the creation and exchange of user-generated content. Social media are defined as a
sales communication tool, consistent with the definition and categories of social media
provided by Kaplan and Haenlein (2010), who looked at tools involving user generated and
co-created content such as social networking sites (e.g., LinkedIn, Facebook, Instagram,
Twitter etc.). Mangold and Faulds (2009) highlight the importance of social media for various
components of a company's integrated marketing communications strategy, including direct
customer communication such as personal selling.

Agnihotri et al. (2016) produced one of the first empirical studies to highlight and
theoretically explain the role of communications mediated by social media in B2B. In the
sales context, consumers use social media as part of their information search process to
investigate the market, compare products and offerings, and establish relationships with
salespeople (Nunan et al., 2018). Agnihotri et al. (2012) approach sales through the lens of a
previous framework focusing on social media use by salespeople, which captures how
technology aids salespeople in maximizing customer value. The authors point out that social
media use augments salespeople's ability to assist buyers by improving the overall flow of
information, which in turn influences satisfaction. Guenzi and Njissen (2020) find evidence of
a direct link between the level of social media use by salespeople in their work and their sales
performance. They show that salespeople who use digital media to a greater extent in their
communication mix are more effective and efficient than their counterparts who make less use of these new tools. Möller (2013) and Gebauer et al. (2013) emphasize the role of social exchanges and their processes within networks as central to value creation. Quinton and Wilson (2016) suggest that a social media network such as LinkedIn acts as an effective relationship initiator. Enyinda et al. (2020) show that managers are increasingly focusing on leveraging Facebook, LinkedIn and Twitter to drive sales processes and in turn boost business performance.

Social media can be used at all stages of the sales process, from prospecting to relationship monitoring. Moore et al. (2015) find that salespeople deploy social media to support the various tasks they are responsible for in the sales process, from prospecting and handling objections to closing and follow-up. Inks et al. (2012) and Moore et al. (2015) suggest that social media offer salespeople new approaches for reaching potential customers. Social media are considered to be an essential part of a company's sales process because they allow salespeople to interact with customers, and create social capital that encourages them to interact, engage and build customer relationships (Agnihotri et al., 2012). Social media such as LinkedIn may help identify genuine decision-makers and buyers within an organization. Itani et al. (2017) argue that both sales management and salespeople view social media as an effective global tool for increasing connectivity and building personal and long-term relationships with customers. Our approach considers how social media provide increased opportunities for customer contact (Hennig-Thurau et al., 2010) and facilitates the behavioral processes in which these tools are aligned with the “relationship forging tasks” necessary for the technology to be effective (Hunter and Perreault Jr, 2007).

## Relationship Marketing and Relational Mediators in B2B Sales

Relationship marketing is well established in B2B sales (Guenzi et al., 2007). Morgan and Hunt (1994) define relationship marketing as “all marketing activities aimed at establishing, developing and maintaining good relationships.” Most research and managerial practices assume that relationship marketing efforts generate stronger relationships with customers, thereby increasing seller performance, sales, market share, and profits (Crosby et al., 1990; Morgan and Hunt, 1994). Relationship marketing emphasizes the importance of buyer-seller relationships, that improve the efficiency of business relationships (Zaheer et al.,
1998) and develop business relationships over the long term (Jap, 2001; Mummalaneni, 1995). As customer demands become more sophisticated and customers themselves become more informed (McDonald and Schrattenholzer, 2001), the sales process is not so much about selling a product as building a relationship (Storbacka et al., 2009). In the age of digital technologies, the B2B sales process is still based on relationships and trust; and to make their purchase decision, buyers take into account recommendations and opinions (Fraccastoro et al., 2021).

In today's business environment, the use of sales support technologies can provide salespeople with the information they need to understand customers and their needs, thus enabling them to tailor their sales behavior accordingly. A new trend seems to be emerging, in that although customers still care about developing trusting relationships with salespeople (Ghanadiof, 2021), they arrange far fewer face-to-face appointments with them. This shift is largely due to the wealth of information available to customers on the Internet. They feel less obligated to meet with salespeople when the answers to their questions are just a click away. In this changing world, salespeople have to adapt their practices to their customers and find other solutions for maintaining a buyer-seller relationship.

Social media use could be a strategy for developing and maintaining salespeople's social proximity with buyers. Proximity is a concept that is typically addressed in the context of innovation, as it plays an important role in promoting trust and understanding when conducting complex and high-risk innovation activities (Fu et al., 2012). Social proximity corresponds to the perception of being psychologically close to (or distant from) other individuals (Aron et al., 1992) perceived as sharing (or not) references and perspectives (Hubert, 2012). Social proximity refers to "the issue of the strength of interpersonal links, in particular to what extent people know each other and interact in private or professional contexts" (Huber, 2012: p.1171). Strong social proximity can foster the development of creativity by establishing a climate of trust and support (Krackhardt, 1992). As Lis (2020: p. 118) notes, social proximity—which was previously underestimated—is currently the second most important dimension of proximity in terms of the number of studies published. The approach to social proximity that we subscribe to is more cognitive than behavioral (Kelley et al., 1983). Two people can, in fact, feel close to each other without interacting frequently
(Dampérat et al., 2016). In the organizational literature, social proximity is defined as the perceived social ties between an individual and his or her co-workers (Hubert, 2012).

Integrating prospecting, sales and a long-term vision, the definition of relationship marketing established by Berry (1983) and Morgan and Hunt (1994) is the most complete. It corresponds to “[a]ny activity aimed at attracting, maintaining and strengthening the relationship between actors”. The quality of the relationship between buyer and seller is recognized as a key relational mediator, and is conceptualized in terms of three dimensions: (1) trust, i.e. confidence in an exchange partner’s reliability and integrity (Doney and Cannon, 1997); (2) commitment, i.e. the enduring desire to maintain a valued relationship (Anderson and Weitz, 1992); and (3) relationship satisfaction, i.e., the customer’s affective or emotional state toward a relationship, typically evaluated cumulatively over the history of the exchange (Crosby et al., 1990). Overall, relationship quality is defined as an assessment of the strength of a relationship. It is conceptualized as a composite or multidimensional construct capturing the different but related facets of a relationship (Palmatier et al., 2006; Wulf et al., 2001).

## Emotional Management in B2B Sales

Emotions are inherent in the connections created by interactions with salespeople (Singh and Venugopal, 2015). Kemp et al. (2018) highlight the importance of emotions in decision-making and infer that marketing communication can be a variable tool for promoting a connection between buyers and suppliers. The “mental capacity” approach to emotional intelligence, developed by (Salovey and Mayer, 1990), refers in part to the ability to recognize the meaning of emotions, and to adapt to the environment or person in order to solve problems (Mayer et al., 1999). The ability to read emotions is defined not by a single “trait” or “feeling”, but rather as a distinct ability to reason and use emotion to achieve desired outcomes (Kidwell et al., 2007). For example, salespeople are more likely to succeed when they do not let their own emotions influence their behavior after a lost sale or poor presentation, and this in turn will prevent “negative emotions” arising when visiting their customers (Strutton and Pelton, 1998).

According to Mayer and Salovey (1997), emotional intelligence is composed of two dimensions, one experiential, the other strategic. The experiential dimension corresponds to
the ability to perceive and manipulate emotional information and to respond to it without
necessarily understanding it. The strategic dimension refers to the ability to understand and
manage emotions without necessarily perceiving feelings or fully experiencing them. This
dimension refers to the salesperson's ability to remain calm in the presence of negative
emotions and to positively influence the customer's emotional reactions (Mayer et al., 2004).
Emotional management is part of this second dimension, which is particularly important in
B2B sales, as it represents the ability of the salesperson to manage the buyer's emotions.
Emotional management is defined as the ability to manage one's emotions and those of others
in order to achieve a desired outcome (Mayer and Salovey, 1997). In other words, emotional
management is related to the reflexive regulation of emotions and concerns the ability to
manage an emotion according to its usefulness in a given situation.

Conceptual Model and Hypothesis Development

Salesperson Performance and Social Media Use

While sales support technologies free up time for sales reps by reducing repetitive tasks, they also provide additional resources for performing abstract and creative tasks (Cirillo et al., 2020). Indeed, salespeople are often confronted with complex sales processes involving multiple actors, and have to find new and original solutions to meet the needs of the customer and close the sale. Moreover, it is now necessary to evaluate the performance of the salesperson not only with regard to his/her performance in terms of sales, but also in terms of creative performance. In this paper, salesperson performance is thus conceptualized as the association of sales performance and creative performance. We define salesperson performance as the extent to which technology affects the salesperson's ability to produce good sales results (Sundaram et al., 2007: p 104). Achieving sales objectives in terms of both quality and quantity variously involves generating new customers, meeting specific sales objectives, improving territorial penetration, and selling profitable products. According to Zallocco et al. (2009) firms look beyond the transaction-based concepts of unit sales and immediate revenue when measuring and evaluating sales performance. Creative performance is defined as the salesperson's ability to develop original solutions to meet the specific needs of each customer (Wang and Netemeyer, 2004: p 806). In the context of industrial selling, buyers use social media for their purchases by comparing products, researching the market,
and building relationships with sellers. Social media are becoming major players in all types
of communication, particularly in B2B, and create unique potential for better salesperson
performance. We thus postulate that salesperson performance is improved by the use of social
media.

H1: Social media use positively influences salesperson performance.

Social proximity and Social Media Use

Social media attract people through the way they present information—namely in
conversations and links, rather than in very formal databases and news outlets (Georgescu and
Popescul, 2015). In this user-friendly and easily accepted environment, created in such a way
as to easily capture unstructured information and knowledge from multiple experiences,
salespeople and buyers can communicate more easily, thereby opening up channels for
knowledge transfer. Traditionally, salespeople have operated at the intersection of social
networks and sales organizations to create value for their customers (Agnihotri et al., 2012).
According to Agnihotri et al. (2012), social media can bring customers and salespeople closer
together in a virtual environment that supports “here” and “now” relationships with faster and
more simultaneous social exchanges. Thus, the use of social media should influence the social
proximity between salespeople and their customers, where social proximity is the perception
of being psychologically close to (or distant from) other individuals (Aron et al., 1992).

H2: Social media use positively influences social proximity.

Relationship Quality and Social Media Use

According to Mullins et al. (2014) relationship quality perceived by the seller as a
combination of the seller's perception of the customer's trust, satisfaction, and commitment to
the firm. Previous studies (Palmatier et al., 2006) show that relationship quality is based on
three dimensions: commitment (Jap and Ganesan, 2000), trust (Palmatier et al., 2006) and
satisfaction (Crosby et al., 1990). We use sellers' perception of relationship quality, as they
know the real level of customers' relational characteristics (Vosgerau and Anderson, 2004).
According to Ellis and Beatty (1995), customers obtain social benefits when salespeople
connect with them at a personal level (i.e., social behavior). We hypothesize that social media should increase buyer-seller connections and help build trust and commitment.

H3: Social media use positively influences relationship quality.

### Relationship Between Relational Mediators

According to the pioneering research of Granovetter (1973), the weaker the social proximity, the broader the base of references to which the team has access and therefore the more creative it needs to be. In contrast, strong social proximity can foster the development of creativity by establishing a climate of trust and support (Krackhardt, 1992). As participants experience higher (lower) levels of social proximity, they feel closer to (more remote from) their counterparts, hence they are more (less) likely to associate and identify with them. Indeed, social proximity has been shown to be an important element in the establishment of trust (Nguyen et al., 2020). Thus, social proximity should lead to a better quality of relationship between buyers and sellers.

H4: Social proximity positively influences relationship quality.

### Relational Mediators and Salesperson Performance

Social proximity can facilitate the selection of business partners (Hegde and Tumlinson, 2014), as individuals tend to have better access to and information about opportunities within their social networks. After forming a partnership, a feeling of social closeness can improve coordination and follow-through among socially close individuals, and social proximity can positively influence salespeople's performance (Hegde and Tumlinson, 2014). Social media as a source of information should result in better performance by the salesperson. Thus, we postulate the positive influence of social proximity on salesperson performance.

H5: Social proximity positively influences salesperson performance.

According to Palmatier et al. (2006), relationship marketing is based on the assumption that building strong relationships positively influences the outcome of exchanges, and researchers recognize that exchanges range across a spectrum from transactional to relational
(Anderson and Narus, 1991). Providing improved benefits in turn prompts customers to repeatedly buy the products offered by the seller, to do more business with the seller by purchasing additional products, and to recommend the products to others. Thus, we expect relationship quality to have a positive impact on salesperson performance.

H6: Relationship quality positively influences salesperson performance.

## The Mediating Effects of Relational Mediators

Social proximity is based on socially embedded relationships between agents based on friendship, kinship, and experience (Li et al., 2013). It enhances the ability of organizations to learn from each other and to innovate. In a business interaction, the effective use of social media improves the seller's ability to anticipate and respond to buyers' concerns and objections, and in turn builds relationships and increases salesperson performance.

H7: (a) Social proximity and (b) relationship quality have parallel mediating effects between social media use and salesperson performance.

## The Moderating Role of Emotional Management

Managing emotions concerns the ability to discover and implement effective strategies using one's emotions to help achieve goals, rather than being subject to one's emotions (Mayer and Salovey, 1997). In the context of relational sales, this dimension implies that the seller is able to maintain his/her composure in the presence of negative emotions and to positively influence the emotional reactions of the customer. For example, a salesperson who manages his/her emotions well can increase the customer's enthusiasm while decreasing the customer's frustration and anxiety (Mayer et al., 2004). From this standpoint, salespeople who are competent in emotional management can further increase customer enthusiasm, increase positive evaluation of products or services, and reduce customer frustration and anxiety (Kidwell et al., 2011). Ultimately, the seller creates a bond of trust and builds a relationship with the customer, based on benevolence. The seller adept at emotional management controls his/her negative emotions, thus having a positive effect on the customer relationship.
H8: Emotional management plays a moderating role in the relationship between social media use and relationship quality.

Salespeople with good emotional management can more easily understand the emotions of others and therefore should be able to create stronger social proximity. This means that understanding emotions and becoming more emotionally intelligent will enable salespeople to become more effective within the workplace (Brown, 2014). Thus, salespeople are able to improve social proximity with their customers by understanding them emotionally more effectively.

H9: Emotional management plays a moderating role in the relationship between social media use and social proximity.

## INSERT FIGURE 1

### Methodology

#### *Sample description*

To test the hypotheses, a survey was conducted among French B2B salespeople from various industries. The participants responded to a survey to evaluate their social media use, social proximity, relationship quality, emotional management, and salesperson performance. 196 completed responses from French B2B salespeople were collected via the Qualtrics platform and a Qualtrics panel (online panel company). Sales professionals were made aware that the research was being conducted for scholarly purposes.

Demographic characteristics of the respondents are presented in Table 1. The age of the respondents ranged from 18 to over 65 years, with the largest age category being aged 25 to 44. The sample was 44.9% male and 54.6% female (0.5% did not respond). The average tenure of the salespeople surveyed was 11.5 years (SD: 9.2), with tenure ranging from 3 months to 42 years. The average annual salary ranged from €30-40k, with a minimum of €20k and a maximum of over €90k. The average use of social media was “more than once a week”, ranging from “never” to “several times a day”. The main business sectors represented are: Trade and Commerce (33.2%); Industry (22.5%); Services (21%); Banking and Insurance (14.1%).
## Data collection procedure

As recommended by Delacroix et al. (2020, p.74), we organized the questionnaire into thematic blocks, with five blocks in total. The structure of the questionnaire was as follows: (1) filter questions related to the job (i.e., age, job title, seniority, and industry); (2) questions related to interpersonal mechanisms (i.e., relationship quality and social proximity); (3) questions related to salesperson performance (i.e., creative performance and sales performance); (4) questions related to the use of social media; and (5) questions related to emotional management. We separated each construct with a new introductory and/or contextualizing sentence (Hulland et al., 2018).

In order to reduce the risks related to method bias and to ensure that respondents are attentive, manipulation checks need to be implemented (Paas and Morren, 2018). We therefore verified that all the respondents successfully answered an instructional check (Oppenheimer et al., 2009) to ensure that they had actually read the questions. The test question was “If you are reading this question please check, ‘somewhat agree’.”

## Measurement Scales

All measures used in this study were adapted from prior research. Descriptive statistics of the variables included in the analyses are presented in Appendix A. All the constructs were assessed using seven-point Likert-type scales ranging from “strongly disagree” (1) to “strongly agree” (7), with the exception of emotional management that was assessed using five-point scales ranging from “not at all effective” (1) to “extremely effective” (5). Appendix B provides the codifications and wording for all items.

For social media use (SMU), we used a 3-item 7-point scale adapted from Agnihotri et al. (2016). The social proximity scale (PROX) comes from the work of Aron et al. (1992). In accordance with our conceptualization, the subjective perception of proximity is represented by a Venn diagram (Aron and Aron, 1986), termed the scale of inclusion of the other in the self. This figurative scale includes a six-point item, with each point representing the overlap of two circles (from 1 for no overlap to 6 for almost complete overlap). It is appropriate for measuring the degree of social closeness and has good convergent and discriminant validity
with other closeness scales (Aron et al., 1992). It has also been taken up by Liu and Gal (2011) and Dampérat et al. (2016) to measure the relationship between an individual and a group. For relationship quality (RQ) as perceived by the salesperson, following Holloway et al. (2013), we use a measure of relationship quality perceived by the salesperson. The items are adapted from the work of Mullins et al. (2014) and consider the three dimensions of relationship quality (i.e., trust, satisfaction, and commitment). Each dimension is composed of two 7-step Likert-type items. In a meta-analysis based on a review of 116 articles, Churchill et al. (1985) found that salespeople's self-assessments of their performance were no worse or better than those of their managers. Sharma et al. (2004) show that salespeople's self-assessment measures of performance are no more biased than those of their managers. We therefore consider that salespeople, who know their customers well, are able to offer a fair assessment of the quality of their relationship with them. For salesperson performance, we used a two-dimensional scale with a dimension relating to sales performance with 3 items of 7 points adapted from Román and Rodríguez (2015) and Behrman and Perreault Jr (1982) and a dimension relating to creative performance with 3 items of 7 points adapted from Wang and Netemeyer (2004). For emotional management (EM), we computed the average of the 4-item 5-point scale from the manage facet of the Emotional Intelligence in Marketing Exchanges (EIME) scale developed by Kidwell et al. (2011). An EIME score is based on IQ score, which means that a score below 69 = *Extremely low*; 70-79 = *Very low*; 80-89 = *Low average*; 90-109 = *Average*; 110-119 = *High average*; 120-129 = *Very high*; 130 and above = *Extremely high*.

INSERT TABLE 2

Data Analysis

To test the proposed model, we used structural equation modeling (SEM). The SEM method offers a generalization of regression that allows the simultaneous testing of multiple levels of analysis from a confirmatory perspective (Evrard et al., 2009). In the case of complex modeling with multiple mediations, structural equation modeling is also preferable to regressions associated with the Macro PROCESS test (Preacher and Hayes, 2004, page 722).

Regarding sample size, Hair et al. (2019, pages 132-133) propose three guidelines based on:
(1) The absolute size of the data set. In the case of hard-to-reach populations, the authors allow a degree of tolerance on the sample size. Our sample size of 196 professional salespeople is therefore considered acceptable in absolute terms.

(2) The ratio of respondents to observed variables. The general rule is to have at least ten times more observations than the number of variables to be analyzed. For our study, the ratio is greater than 10:1 (196:18, or 10.88), and is therefore acceptable. If the 10:1 ratio is achieved, the results should be generalizable as long as the sample is representative (Hair et al., 2019 page 279).

(3) The “strength” of the analysis results. Following McQuitty’s (2004) decision rules, to obtain statistical power greater than 0.80 with a model with more than 100 degrees of freedom, a sample size greater than 132 observations must be gathered. Our model has 120 degrees of freedom, highlighting its high statistical power. We also tested the robustness of our modeling by performing a Bollen-Stine bootstrap test based on creating 200 bootstrap samples. We obtain p = 0.100, which is above the 0.05 significance level. Thus, there is no statistically significant difference between the pre-bootstrap and post-bootstrap estimates. The model is therefore robust and has a good fit to the data. In view of our sample size, the structural equation modeling is therefore considered acceptable.

## Results

### Measurement Evaluation

To assess the quality of the measurement scales, we followed a two-step procedure following the recommendations of Steenkamp and Van Trijp (1991). The first step was to study the correlations in order to purify the scales. Items with correlations less than 0.30 were removed. The second step consisted of a confirmatory factor analysis (CFA) evaluated on the basis of the indices recommended by Hu and Bentler (1998). For the multi-item scales included in the measurement model, the tests of reliability and convergent and discriminant validity show good results (see Table 1). Based on these recommended indices, the measurement model is satisfactory: Chi²/81 = 1.504; RMSEA = 0.05; TLI = 0.962; CFI = 0.971; SRMR = 0.059. The standardized parameters, standard errors, t-test and p-value of each item are presented in Appendix B.
The analysis of reliability, convergent validity, and discriminant validity shows the satisfactory results for each construct. The convergent validity of the constructs is confirmed with average variance extracted (AVE) values greater than 0.50, and AVE estimates for all respective pairs of constructs in the model are greater than their matching squared correlations, in accordance with the recommendations of Fornell and Larcker (1981). Likewise, discriminant validity is established, since the average variance extracted from each construct is greater than the correlation squares, which are well below the threshold of 0.50. The detailed results are presented in Table 2. To test for common method bias, we conducted a Harman single-factor test (Podsakoff and Organ, 1986). The proposed model presents a total explained variance of 84.0% for 7 factors versus 33.3% for a single factor, which is less than the 50% threshold (Fuller et al., 2016; Podsakoff et al., 2003; Podsakoff and Organ, 1986). This result suggests that common method bias does not affect the findings.

### Direct Effects Testing

The proposed model and its related hypotheses (H1 to H6) were tested using structural equations with the maximum likelihood method with AMOS 27. Based on Hu and Bentler (1998) indices, the structural model is satisfactory (see Table 3 for the detailed results): $Chi²/120 = 1.536; RMSEA = 0.05; TLI = 0.956; CFI = 0.965; SRMR = 0.059$. Results show that social media use positively and significantly influences salesperson performance (H1: $γ = 0.34$; $p = 0.000$). Social media use also positively and significantly influences relationship quality (H2: $β = 0.23$; $p = 0.006$) and social proximity (H3: $β = 0.15$; $p = 0.046$). Thus, H1, H2 and H3 are confirmed. Social proximity positively and significantly influences relationship quality (H4: $β = 0.19$; $p = 0.015$), confirming H4. Salesperson performance is positively and significantly influenced by relationship quality (H5: $β = 0.49$; $p = 0.000$) but not by social proximity (H6: $β = 0.14$; $p = 0.083$). H5 is therefore confirmed and H6 is not.

### INSERT TABLE 3

### Mediating Effects Testing

Regarding the mediating role of social proximity and relationship quality, we followed the recommendations of Zhao et al. (2011) and of Preacher and Hayes (2004), leading us to perform the bootstrap test of the indirect effect via structural equations modeling. The results show that the indirect effect of social media use on relationship quality through social
proximity is not significant (b = 0.03; p = 0.065). On the other hand the indirect effect of
social proximity on salesperson performance through relationship quality is statistically
significant (b = 0.09; p = 0.028), with a 95% confidence interval (b between 0.023 and 0.191)
excluding the value zero. Likewise, the indirect effect of social media use on salesperson
performance through both social proximity and relationship quality is statistically significant
(b = 0.15; p = 0.010; with b between 0.060 and 0.256). H7 is partially confirmed. Table 4
presents the results for the indirect effects of social media use on salesperson performance.

INSERT TABLE 4

Testing of Moderating Effects

Following the recommendations of Ping Jr (1995), as in a standard regulation, it is
necessary to test the moderating effect by: (1) creating two new variables, one corresponding
to the centered mean of the observed variables of the exogenous variable (mcX), and the other
to the centered mean of the observed variables of the moderating variable (mcM); (2)
calculating the product of the indicators between the centered mean of the exogenous variable
and the centered mean of the moderating variable; (3) testing the complete model by
regressing the endogenous variable on the product of the indicators as well as the simple
linear effects of the exogenous variable and the moderating variable in their latent form.

For the moderating effect to be proven, the relationship between the endogenous
variable on the product of the indicators must be significant and in the direction expected by
the hypothesis. The moderating effect of emotional management on the relationship between
social media use and relationship quality is statistically significant (H8: β = -0.20; p = .012).
H8 is therefore confirmed. The moderating effect of emotional management on the
relationship between social media use and social proximity is not significant (H8: β = -0.03; p
= .741). H9 is rejected.

To analyze the moderation effect of emotional management (H8) in greater detail, we
used the Johnson-Newman floodlight method (Spiller et al., 2013) from the Model 1 of the
Hayes macro PROCESS for SPSS (Preacher and Hayes, 2004). We chose Model 1 in order to
focus our study on the moderating mechanism only. The advantage of this method is that it
can identify the values of the moderator (i.e., emotional management) for which the
interaction is statistically significant. First, we computed the average for the three items of social media use (SMU), the four items of emotional management (EM), and the six items of relationship quality (RQ). Second, we calculated the average of all independent variables and mean-centered them. Third, we performed the moderated regression model on SPSS, the results of which are presented in Figure 2. The significance of the slope of social media use on relationship quality was examined at several points (EM Low = m-σ; EM Moderate = m; EM High = m+σ) of emotional management. For values of emotional management higher than 115 (corresponding to the average of EI score for the general population), the simple slope of social media use was not statistically significant. In contrast, it was statistically significant for values below 115 for emotional management. These results allow us to detail the moderating role of emotional management, because the positive effect of social media use on relationship quality occurred only for individuals with low emotional management abilities, but not for those with high emotional management abilities.

INSERT FIGURE 2

Discussion

The main objective of this study was to better understand the role of social media use on salesperson performance in B2B settings, especially through relational mediators and the salesperson's emotional management. The results confirm our proposed model, as most of the hypotheses were confirmed. Consistently with our hypotheses, the use of social media has a positive and direct influence on salesperson performance, and an indirect influence through social proximity and relationship quality, showing parallel mediation effects. Our results also show a significant moderating effect of the salesperson's emotional management on the relationship between social media use and relationship quality.

The results show that the use of social media by salespeople increases their performance both directly and indirectly, in line with the recent study by Guenzi and Njissen (2020). The direct influence means that social media use provides accurate and relevant information on customers' needs and profiles, and that it is an important tool for hitting the market run in B2B settings. As previously shown by Itani et al. (2020), social media are valuable enablers of the buyer-seller interface. The indirect influence indicates that the more salespeople use social networks, the more they improve their social proximity to customers' requirements, improve the quality of their relationship with customers and in turn augment their own
performance. Our study provides evidence that the use of social media in B2B increases salesperson performance.

Surprisingly, social proximity does not directly improve salesperson performance, but has only an indirect influence on it through relationship quality. Marshall et al. (2012) found that sales managers and salespeople view social media as an effective tool for increasing connectivity, building personal and long-term relationships with customers, and maintaining relationships in general. However, our results show that the use of social media has a direct effect on the buyer-seller relationship quality.

Exploring more closely the relationship between the salesperson's social media use and the quality of the buyer-seller relationship, we show the moderating effect of the salesperson's ability to successfully manage other people's emotions. For salespeople with low to moderate emotional management abilities, an increase in their use of social media improves the quality of their relationship with the buyer. However, for salespeople with higher than average emotional management abilities, the use of social media does not influence their relationship quality with the buyer. In line with Marshall et al. (2012), our results show that social media use positively influences relationship quality, but that this is true only for salespeople with low to moderate emotional management abilities. It seems that salespeople with high emotional management skills do not need social media to create a high-quality relationship with their customers.

## Theoretical implications

In line with Bolander et al. (2021) on measurement performance, we considered a more complete measure of salesperson performance adapted to the context of complex sales. Our approach combined *sales performance* and *creative performance*, thereby allowing a more refined measurement of salesperson performance. Doing so allowed us to better understand the diversity of performance achieved by the salesperson in the course of his or her missions. Selling in B2B is complex and requires the salesperson to take into consideration many constraints (Bolander et al., 2021). Thus, considering the creative performances of the salesperson allowed us to account for his or her creative problem-solving capacities and thus preparation for future sales.
Our study extends the sales literature by examining the effects of two important variables, i.e. relationship quality and social proximity, in enhancing the effectiveness of salespeople's social media use. From a theoretical standpoint, the use of social media platforms improves relationship quality and social proximity with customers. However, we identify the role of emotional management as a boundary condition. Our study shows the strong positive influence of social media use on salesperson performance. By incorporating emotion management, we present an integrated model of salespeople's social media use and enhance the current understanding of this important area of inquiry in sales research, with the implication that not all salespeople obtain the same results in terms of relationship management when using social media. Indeed, it seems that a differentiated study of salespeople according to their emotional management profile (high vs. low) is necessary to better understand the mixed findings of work on emotional management.

## *Practical Implications*

In a world of profound change, with many transitions underway, salespeople need to adapt to these new constraints (Hartmann and Lussier, 2020). This broadened measure of performance includes results in terms of adaptability and searching for new solutions that ultimately lead to the creation of new business opportunities. This new conceptualization invites sales managers to consider an approach that is more appropriate to the complexity of B2B sales, and that also allows for a greater appreciation of the salesperson's skills.

From a managerial standpoint, our results support the importance of the use of social media by salespeople. On the other hand, salespeople, must to agree to take the time to train in the use of social media and the associated codes. This entails changing their practices and routines. Social media can help salespeople create social proximity with their customers and thus improve the quality of the relationship and ultimately their performance. Social media also provide salespeople with increased visibility and can help them to build relationships with potential customers and reach out to new leads. By creating profiles on social media sites, salespeople can increase their reach and attract new customers. Moreover, salespeople with low to moderate skills in managing other people's emotions benefit greatly from the use of social media, because it directly improves their relationship with customers. In other words, salespeople with low to medium emotional management abilities should invest time on social media in order improve the quality of their relationship with customers, but those with
high emotional management abilities do not need to invest much time on social media because the return on the investment would not be worth it. In this regard, they can use the information collected to better manage the customer relationship. However, many B2B salespeople are uncomfortable with digital tools and using social media (Agnihotri et al., 2021). To overcome these challenges, salespeople need to be trained in the use of social media, change their practices and routines, and use the information gathered to better manage customer relationships. Sales management also has an important role to play in helping salespeople adopt and make the most of social media. Managers should therefore encourage the use of social media by salespeople and monitor new social media uses.

Based on our findings, we recommend that managers monitor and develop their salespeople's empathy skills and use of social media. It seems beneficial to train their sales teams and to support them in their use of social media. Terho et al. (2022) show new evidence that management plays a central role in boosting social selling by the sales force through social media strategy, social media sales tools, and firm content support. We also suggest that management should ensure that their sales teams are trained and coached to make the most of social media. It is particularly important to accompany salespeople during periods of change to avoid overloading and ensure high satisfaction and performance.

## Limitations and Research Perspectives

There are various limitations to our study that may affect the reliability of the results. First, all measures were self-reported by the salesperson. While a dyadic sample would be preferable, sample accessibility was limited to sellers only. However, Agnihotri et al. (2016) argue that “in general contact employees are good sources of information on customer attitudes (Bitner et al., 1994) and a perceptual measure can be used when an accurate objective measure is not available (Dess and Robinson Jr, 1984).” In addition to salespeople’s perceptions, future work should examine the issue from the perspective of sales managers and customers. Such research would provide new insights into the use of social media in a B2B context.

Secondly, our assessment of salesperson performance is structured around two dimensions, i.e., sales performance and creative performance, each of which performs well in terms of reliability and validity. However, compared to the original scales, we redesigned this two-dimensional scale. Our decision was guided, on the one hand, by the need to adapt the
items to our specific study context, and on the other, by a concern for parsimony, leading us
to reduce the number of items for each scale in order to make the questionnaire less
cumbersome, as recommended by Hair et al. (2019). Doing so has the advantage of allowing
the inclusion of the two important, yet understudied, dimensions of salesperson performance
in the same study; but it also constitutes a limitation to our study, which calls for further
investigation to ensure the replicability of the results.

Third, in line with the work of Depechitre et al. (2019), who demonstrated the risk of lower productivity, it might be interesting to explore the implications for the sales force of the rise of social media and the “always-on” communication technology usage patterns associated with them, as well as the “dark side” of the use of social media on salespeople’s job satisfaction. Some salespeople experienced a problem known as “social media fatigue”, in which they feel anxious about being overwhelmed by social media (Han, 2018). Social media are an unfamiliar new tool for some salespeople and can, in this regard, constitute an additional cognitive load and therefore lead to overload, with the accompanying risk of burnout and dissatisfaction at work.

Fourth, we have approached the sales-customer relationship at different stages, from
new business prospecting to long-term relationships, because salespeople are often required to
work on both prospecting and managing customers. It might be interesting to specifically
study the use of social media at each phase of the sales process, in order to further enhance
understanding.

And finally, we have found that it is not enough that salespeople simply use social
media to increase their business performance, but that they need to understand how using
social media can impact the selling process and improve different selling behaviors (such as
adaptive selling behavior), which, in turn, have direct effects on performance. For example, as
Itani et al. (2017) suggest, researchers should try to understand how salespeople use different
social media tools and other CRM technologies at the same time, and the effect that
simultaneous use can have on performance.
Appendix A – Means, Standard Deviation, and Correlation Matrix

<table><thead><tr><th rowspan="2">Items</th><th rowspan="2">Means</th><th rowspan="2">Stand. Errors</th><th rowspan="2">SMUxEM M</th><th rowspan="2">EM</th><th rowspan="2">PROX</th><th rowspan="2">SP_CP3</th><th rowspan="2">SP_CP2</th><th rowspan="2">SP_CP1</th><th rowspan="2">SP_SP3</th><th rowspan="2">SP_SP2</th><th rowspan="2">SP_SP1</th><th colspan="10">Correlation Matrix</th></tr><tr><th>RQ_CO MM2</th><th>RQ_CO MM1</th><th>RQ_SA T2</th><th>RQ_SA T1</th><th>RQ_CO 2</th><th>RQ_CO 1</th><th>SMU1</th><th>SMU2</th><th>SMU3</th></tr></thead><tbody><tr><td>SMUxEM</td><td>-0.37</td><td>1.795</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EM</td><td>2.10</td><td>0.981</td><td>0.261</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PROX</td><td>3.76</td><td>1.526</td><td>0.010</td><td>0.023</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_CP3</td><td>5.39</td><td>1.054</td><td>-0.010</td><td>-0.016</td><td>0.186</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_CP2</td><td>5.21</td><td>1.074</td><td>-0.010</td><td>-0.015</td><td>0.178</td><td>0.555</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_CP1</td><td>5.36</td><td>1.040</td><td>-0.010</td><td>-0.015</td><td>0.178</td><td>0.555</td><td>0.531</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_SP3</td><td>5.14</td><td>1.052</td><td>-0.009</td><td>-0.013</td><td>0.158</td><td>0.340</td><td>0.325</td><td>0.325</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_SP2</td><td>5.24</td><td>1.057</td><td>-0.008</td><td>-0.013</td><td>0.152</td><td>0.327</td><td>0.313</td><td>0.313</td><td>0.637</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SP_SP1</td><td>5.28</td><td>1.005</td><td>-0.008</td><td>-0.013</td><td>0.150</td><td>0.322</td><td>0.308</td><td>0.308</td><td>0.627</td><td>0.603</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_COM M2</td><td>4.51</td><td>1.345</td><td>-0.065</td><td>0.039</td><td>0.113</td><td>0.188</td><td>0.180</td><td>0.180</td><td>0.161</td><td>0.154</td><td>0.152</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_COM M1</td><td>5.35</td><td>1.278</td><td>-0.090</td><td>0.054</td><td>0.157</td><td>0.262</td><td>0.250</td><td>0.250</td><td>0.223</td><td>0.215</td><td>0.211</td><td>0.612</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_SAT2</td><td>5.60</td><td>1.088</td><td>-0.099</td><td>0.059</td><td>0.173</td><td>0.287</td><td>0.275</td><td>0.275</td><td>0.245</td><td>0.236</td><td>0.232</td><td>0.396</td><td>0.551</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_SAT1</td><td>5.66</td><td>1.109</td><td>-0.096</td><td>0.057</td><td>0.167</td><td>0.279</td><td>0.267</td><td>0.266</td><td>0.238</td><td>0.229</td><td>0.225</td><td>0.384</td><td>0.534</td><td>0.747</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_CO2</td><td>5.90</td><td>1.123</td><td>-0.082</td><td>0.049</td><td>0.143</td><td>0.238</td><td>0.228</td><td>0.228</td><td>0.203</td><td>0.195</td><td>0.192</td><td>0.329</td><td>0.457</td><td>0.501</td><td>0.486</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RQ_CO1</td><td>5.77</td><td>1.065</td><td>-0.089</td><td>0.053</td><td>0.155</td><td>0.259</td><td>0.247</td><td>0.247</td><td>0.220</td><td>0.212</td><td>0.209</td><td>0.356</td><td>0.496</td><td>0.544</td><td>0.528</td><td>0.726</td><td>1.000</td><td></td><td></td><td></td><td></td></tr><tr><td>SMU1</td><td>4.31</td><td>2.010</td><td>0.124</td><td>-0.181</td><td>0.128</td><td>0.270</td><td>0.258</td><td>0.258</td><td>0.230</td><td>0.221</td><td>0.218</td><td>0.094</td><td>0.130</td><td>0.143</td><td>0.138</td><td>0.118</td><td>0.128</td><td>1.000</td><td></td><td></td><td></td></tr><tr><td>SMU2</td><td>4.18</td><td>1.968</td><td>0.126</td><td>-0.184</td><td>0.130</td><td>0.273</td><td>0.261</td><td>0.261</td><td>0.233</td><td>0.221</td><td>0.221</td><td>0.095</td><td>0.132</td><td>0.145</td><td>0.140</td><td>0.120</td><td>0.130</td><td>0.904</td><td>1.000</td><td></td><td></td></tr><tr><td>SMU3</td><td>4.32</td><td>2.069</td><td>0.124</td><td>-0.182</td><td>0.128</td><td>0.270</td><td>0.258</td><td>0.258</td><td>0.230</td><td>0.221</td><td>0.218</td><td>0.094</td><td>0.130</td><td>0.143</td><td>0.139</td><td>0.119</td><td>0.129</td><td>0.893</td><td>0.905</td><td>1.000</td><td></td></tr></tbody></table>
Appendix B – Results of the Measurement Model

<table><thead><tr><th>Codifications</th><th>Wording</th><th>λ stand.</th><th>σ</th><th>t-test</th><th>p value</th></tr></thead><tbody><tr><td colspan="6"><strong>Social Media Use (a)</strong></td></tr><tr><td>SMU1</td><td>I am using sales force technology tools to its fullest potential for supporting my own work.</td><td>0.94</td><td>-</td><td>-</td><td>-</td></tr><tr><td>SMU2</td><td>I am using all capabilities of sales force technology tools in the best fashion to help me on the job.</td><td>0.96</td><td>0.04</td><td>28.67</td><td>0.000</td></tr><tr><td>SMU3</td><td>My use of sales force technology tools is pretty much integrated as part of my normal work routine.</td><td>0.95</td><td>0.04</td><td>27.31</td><td>0.000</td></tr><tr><td colspan="6"><strong>Social Proximity (b)</strong></td></tr><tr><td>PROX</td><td>What degree of proximity (or distance) do you perceive between yourself ("self") and your customers and/or prospects ("others")?</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td colspan="6"><strong>Relationship Quality (a)</strong></td></tr><tr><td colspan="6"><em>Trust Dimension</em></td></tr><tr><td>RQ_CO1</td><td>My customers perceive me to be very trustworthy.</td><td>0.89</td><td>-</td><td>-</td><td>-</td></tr><tr><td>RQ_CO2</td><td>My customers perceive me to be honest in all our transactions.</td><td>0.82</td><td>0.09</td><td>11.09</td><td>0.000</td></tr><tr><td colspan="6"><em>Satisfaction Dimension</em></td></tr><tr><td>RQ_SAT1</td><td>Overall, I think my customers are very satisfied with me.</td><td>0.85</td><td>-</td><td>-</td><td>-</td></tr><tr><td>RQ_SAT2</td><td>Overall, I think my customers enjoy working with me.</td><td>0.88</td><td>0.08</td><td>12.71</td><td>0.000</td></tr><tr><td colspan="6"><em>Commitment Dimension</em></td></tr><tr><td>RQ_COMM1</td><td>My customers are determined to maintain our relationship for the long term.</td><td>0.92</td><td>-</td><td>-</td><td>-</td></tr><tr><td>RQ_COMM2</td><td>My customers would be willing to make sacrifices to preserve our relationship.</td><td>0.66</td><td>0.10</td><td>7.88</td><td>0.000</td></tr><tr><td colspan="6"><strong>Salesperson Performance (a)</strong></td></tr><tr><td colspan="6"><em>Sales Performance Dimension</em></td></tr><tr><td>SP_SP1</td><td>I am getting sales results that exceed expectations.</td><td>0.77</td><td>-</td><td>-</td><td>-</td></tr><tr><td>SP_SP2</td><td>I exceed the sales targets set for the year.</td><td>0.78</td><td>0.11</td><td>10.21</td><td>0.000</td></tr></tbody></table>
<table><tr><td>SP_SP3</td><td>I have excellent sales performance.</td><td>0.81</td><td>0.11</td><td>10.43</td><td>0.000</td></tr><tr><td colspan="6"><strong>Creative Performance Dimension</strong></td></tr><tr><td>SP_CP1</td><td>I frequently find original solutions to problems.</td><td>0.73</td><td>-</td><td>-</td><td>-</td></tr><tr><td>SP_CP2</td><td>I often come up with novel solutions to meet clients' needs.</td><td>0.73</td><td>0.12</td><td>8.59</td><td>0.000</td></tr><tr><td>SP_CP3</td><td>I am able to help my clients with new solutions that they had not thought of.</td><td>0.76</td><td>0.12</td><td>8.82</td><td>0.000</td></tr><tr><td colspan="6"><strong>Emotional Management (c) (d)</strong></td></tr><tr><td>EM1</td><td>He could tell his new supervisor how much he didn't like the previous supervisor.</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>EM2</td><td>Call back the customer and criticize him/her for wasting your time.</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>EM3</td><td>Teach the customer a lesson by not returning any of his/her phone calls.</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>EM4</td><td>Bill should accept the fact that the couple probably won't make the purchase.</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></table>

(a) The construct is evaluated using a seven-point Likert-type scales ranging from “strongly disagree” (1) to “strongly agree” (7).

(b) Figurative scale ranging from “distant” to “close”.

(c) The construct is evaluated using a five-point scales ranging from “not at all effective” (1) to “extremely effective” (5).

(d) Following the instructions of the inventors of the EM scale, we perform the average of the items. This average was not included in the measurement model.
<figure><img src="image_2.png" /><figcaption>Appendix C – Measurement Model</figcaption></figure>
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<figure><img src="image_3.png" /><figcaption>Figure 1 – The Proposed Model</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Figure 2 – Interaction Effect between Social Media Use and Emotional Management on Relationship Quality</figcaption></figure>
<table><caption>Table 1 - Demographic characteristics of the sample</caption><tbody><tr><td rowspan="5">Age</td><td>18 and 24 years old</td><td>15.3%</td></tr><tr><td>25 and 34 years old</td><td>28.1%</td></tr><tr><td>35 and 44 years old</td><td>28.1%</td></tr><tr><td>45 and 54 years old</td><td>17.9%</td></tr><tr><td>More than 55 years old</td><td>9.7%</td></tr><tr><td rowspan="5">Company size</td><td>1 to 9 employees</td><td>14.8%</td></tr><tr><td>10 to 49 employees</td><td>21.9%</td></tr><tr><td>50 to 249 employees</td><td>17.9%</td></tr><tr><td>250 to 4999 employees</td><td>27.6%</td></tr><tr><td>More than 5000 employees</td><td>17.9%</td></tr><tr><td rowspan="6">Job Title</td><td>Salesperson</td><td>40.3%</td></tr><tr><td>Sales manager</td><td>27.0%</td></tr><tr><td>Key accounts manager</td><td>4.6%</td></tr><tr><td>Business manager / business developer</td><td>11.2%</td></tr><tr><td>Technical sales</td><td>11.2%</td></tr><tr><td>Business engineer</td><td>5.6%</td></tr><tr><td rowspan="4">Sector</td><td>Trade and Commerce</td><td>33.2%</td></tr><tr><td>Industry</td><td>22.5%</td></tr><tr><td>Services</td><td>21%</td></tr><tr><td>Banking and Insurance</td><td>14.1%</td></tr></tbody></table>
<table><caption>Table 2 - Reliability, Convergent Validity, and Discriminant Validity</caption><thead><tr><th rowspan="2">Constructs</th><th rowspan="2">A.V.E.</th><th colspan="4">Squared correlations</th></tr><tr><th>SMU</th><th>ASB</th><th>RQ</th><th>SP</th></tr></thead><tbody><tr><td>SMU</td><td><strong>0.90</strong> (a)</td><td>0.95 (b)</td><td></td><td></td><td></td></tr><tr><td>ASB</td><td><strong>0.53</strong></td><td>0.11 (c)</td><td>0.73</td><td></td><td></td></tr><tr><td>RQ</td><td><strong>0.72</strong></td><td>0.04</td><td>0.16</td><td>0.84</td><td></td></tr><tr><td>SP</td><td><strong>0.63</strong></td><td>0.16</td><td>0.21</td><td>0.13</td><td>0.79</td></tr></tbody></table>

(a) The average extracted variance by construct is presented in the second column and is in bold.

(b) The alpha coefficients are presented in the diagonal and are in italics.

(c) The squares of the correlations between constructs are presented in the lower triangle.
<table><caption>Table 3 – Results for the Proposed Model</caption><thead><tr><th></th><th></th><th></th><th>Par. stand.</th><th>Stand. Error</th><th>t-test</th><th>p-value</th></tr></thead><tbody><tr><td>H1</td><td>Social Media Use</td><td>→ Salesperson Performance</td><td>0.34</td><td>0.029</td><td>3.912</td><td>0.000</td></tr><tr><td>H2</td><td>Social Media Use</td><td>→ Relationship Quality</td><td>0.23</td><td>0.040</td><td>2.749</td><td>0.006</td></tr><tr><td>H3</td><td>Social Media Use</td><td>→ Social Proximity</td><td>0.15</td><td>0.060</td><td>1.997</td><td>0.046</td></tr><tr><td>H4</td><td>Social Proximity</td><td>→ Relationship Quality</td><td>0.19</td><td>0.046</td><td>2.436</td><td>0.015</td></tr><tr><td>H5</td><td>Relationship Quality</td><td>→ Salesperson Performance</td><td>0.49</td><td>0.074</td><td>4.577</td><td>0.000</td></tr><tr><td>H6</td><td>Social Proximity</td><td>→ Salesperson Performance</td><td>0.14</td><td>0.033</td><td>1.734</td><td>0.083</td></tr><tr><td rowspan="2">H8</td><td>Emotional Management</td><td>→ Relationship Quality</td><td>-0.20</td><td>0.041</td><td>-2.505</td><td>0.012</td></tr><tr><td>X Social Media Use</td><td>→ Relationship Quality</td><td>0.17</td><td>0.046</td><td>2.436</td><td>0.015</td></tr><tr><td rowspan="2">H9</td><td>Emotional Management</td><td>→ Social Proximity</td><td>-0.03</td><td>0.064</td><td>-0.330</td><td>0.741</td></tr><tr><td>X Social Media Use</td><td>→ Social Proximity</td><td>0.06</td><td>0.115</td><td>0.767</td><td>0.443</td></tr><tr><td colspan="7"><strong>Goodness of Fit Measures:</strong></td></tr><tr><td colspan="2">χ² / df</td><td colspan="4">184,358 / 120 (1.536)</td><td></td></tr><tr><td colspan="2">RMSEA</td><td colspan="4">0.052</td><td></td></tr><tr><td colspan="2">TLI</td><td colspan="4">0.956</td><td></td></tr><tr><td colspan="2">CFI</td><td colspan="4">0.965</td><td></td></tr><tr><td colspan="2">SRMR</td><td colspan="4">0.059</td><td></td></tr></tbody></table>
<table><caption>Table 4 – Results for the Indirect Effects of Social Media Use on Salesperson Performance via Relationship Quality and Social Proximity (H8)</caption><thead><tr><th></th><th>Par. stand.</th><th>Lower bounds</th><th>Upper bounds</th><th><i>p-value</i></th></tr></thead><tbody><tr><td>SMU → PROX → RQ</td><td>0.03</td><td>0.002</td><td>0.071</td><td><i>0.065</i></td></tr><tr><td>PROX → RQ → SP</td><td>0.09</td><td>0.023</td><td>0.191</td><td><i>0.028</i></td></tr><tr><td>SMU → PROX → RQ → SP</td><td>0.15</td><td>0.060</td><td>0.256</td><td><i>0.010</i></td></tr></tbody></table>