Does Gender Matter? Effect of Colleagues’ Support on Work Engagement of Salespeople

Abstract

Salespeople suffer from work pressure in their workplace. Hence, an important issue in sales management is how to increase salesperson confidence and motivate them to work harder. This study examines social support from management and peers on sales employees using the stimulus-organism-response (SOR) theory. A cross-sectional survey was then conducted among 140 female and male salespersons from the insurance/financial/retail industries during the pandemic period in Hong Kong. It was found that management support was important for the work engagement of salespeople. Self-confidence can be improved through consultation with managers. Female salespersons prefer sharing their concern with managers from another department, whereas male salespersons opt for managers from the same department. Peer support from sales colleagues of the same department was not preferred. Emotional support for female salespeople and cognitive support for male salespeople should be provided.

1. Introduction

Salespeople often become frustrated for various reasons, such as non-achievement of their personal sales target or that of the company’s sales target or difficulty in reaching the sales team. The effects of these frustrations on salespeople can be serous. It affects their income directly if they work in a commission-based system or indirectly if they work in a fixed salary system. In a fixed salary system, the year-end bonus and incremental rate of salary adjustment might still be affected. Losing confidence or motivation due to frustrations might also affect subsequent performance [1].

Previous studies have concentrated on the relationship between work motivation and sales performance [2,3]. A few studies have shown that a salesperson’s work engagement can be improved [4] It has been suggested that sales managers might guide their team members by coaching [4].

Various resources are available for salespeople, including physical, social and psychological resources [5]. Salespeople could have some basic salary, irrespective of whether they make any sales. The basic salary is an example of physical resources. It offers financial support for basic living expenses, including traveling and food. Other examples of physical resources are administrative, information technology and meeting room support. Salespeople could seek help from their social networks, such as family and friends. Social resources are also available. Psychological resources could be offered by a professional psychological counselor. Other people, such as colleagues, could offer advice based on their knowledge and experience. People might try to gather resources on the one hand, and lose some resources on the other hand. This is known as the concept of conservation of resources [6]. Pressure from the job might lead to exhaustion and loss of job resources are related to work engagement [7].

There are updated studies on work engagement in general [8]. Additionally, there is a recent study on salesperson turnover but not in work engagement [9]. This study focuses on colleagues’ support contribution to the work engagement of salespeople by addressing the literature gap. The stimulus-organism-response (SOR) theory was used as a theoretical basis (Figure 1). The SOR theory has been used in many fields [10]. Stimulus is an external shock which is represented by colleagues’ support in this study. Colleagues’ support includes peer support, manager (superior) support, and support from managers from other departments. The organism is work engagement, while the response is self-evaluation of success.

We have two research questions in the study:

• Which type of colleagues’ support is effective for salespeople?
• Which type of support (immediate supervisor/others) would be more effective for male and female salespersons?

The customer could have better satisfaction when the sales force has better work engagement. More knowledge on the work engagement of salespeople could contribute to a corporation’s survival in the market because the attitude of frontline salespeople affects customer perception of corporate image. The resilience of salespeople was tested during the pandemic crisis; resilience refers to the competence of individuals in a changing environment [11].

2. Literature Review

2.1. Theoretical Framework

Maslow’s hierarchy of needs theory is perhaps the most well-known theory of motivation. The five needs of an individual are highlighted. According to [5], needs can be categorized into five types: physiological, safety, social, esteem, and self-actualization needs. Salespersons need social resources in addition to basic needs such as food, shelter and safety. Salespeople usually have a network of friends which could provide social support. Esteem needs and self-actualization are the next levels that need to be addressed. Esteem factors can be internal and external. Corporations and industry contribute to the external esteem factors, which include recognition, attention, and status. Sales awards are an example of these esteem factors. Self-respect, autonomy, and achievement are internal esteem factors. Finally, achieving their potential and self-fulfillment is part of the self-actualization needs, and a salesperson’s self-evaluation of success is related to these topics.

Salespersons are subject to high pressure externally from customers and competitors. Internally, salespersons need to achieve the set quota and sometimes compete with their peers. Their job demands affect their mental health and stress. Job resources can counterbalance the effects of job demand [12].

There are three parts in the stimulus-organism-response (SOR) theory: Stimulus, organism, and response. Usually, constructs in stimulus are independent variables affecting some other dependent variables in response. Organism is the middle status between stimulus and response [13].

2.2. Work Engagement

The term ‘Work engagement’ is a non-negative, work-related mindset that is determined by work commitment [14]. It has been proved that higher work engagement of employees leads to better performance of the corporations [15]. It has been defined to affective, cognitive, and physical dimensions. Emotion, feeling, and mood are affective experience. Focus, attentiveness, and responsive are cognitive elements. Willingness, desire, and eagerness are conative elements. It has been argued that work engagement is a distinct construct [14].

2.3. Association between Work Engagement and Work Success

There are studies on the relationship between work success and work engagement in the past decades [16]. People who are engaged in their job have better mental health and are more active in their daily work [17].

The engagement–performance link has been validated in empirical studies [18], which suggested that a proactive personality can “predict work engagement and job performance given that engaged workers who are physically, cognitively and emotionally connected to their work roles demonstrate a ‘job crafting’ behaviour through which they may actively change the content or design of their jobs by choosing tasks, negotiating different job content, and assigning meaning to their tasks or jobs” ([18], p. 268).

Work success can be divided into task performance, which refers to in-role performance and required outcomes and behaviors that directly serve the goals of an organization, and contextual performance, which comprises the five components of organizational citizenship behavior, namely, civic virtue, courtesy, altruism, sportsmanship, and conscientiousness ([19], p. 475). Moreover, work engagement is positively related to task performance, contextual performance, and active learning, especially for employees with high conscientiousness (i.e., employees who are inclined to work hard, to be careful, and to be goal-oriented ([20], 2012, p. 1370)

Work engagement positively affects work success, with service climate and job embeddedness playing a mediating role. Work engagement is not only relevant in enhancing the performance of individuals, but can also be managed and developed by antecedents that human resource development practitioners in organizations can provide and enhance [16].

Companies invest in high-performance work practices (HPWPs) in the workplace, as represented by ‘internal career/promotion opportunities, teamwork, employment security, staffing selectivity, work–family balance, training, empowerment and rewards’ to promote work engagement and retain highly engaged employees ([21], p. 132). In a survey of hotel frontline staff and managers in Romania, it has been found that work engagement fully mediates the effects of HPWPs on job performance and that discretionary behavior plays an additional customer service role that extends beyond formal job requirements [21]. Studies on the nursing profession also reveal that the work engagement of nurses is correlated with their work performance and the outcomes of healthcare organizations [22].

Consequently, the following hypotheses are proposed:

Hypothesis 1 (H1).

Work engagement of salespeople is associated with the self-evaluation of work success.

2.4. Association between Peer Support and Work Engagement

Peer support refers to the salesperson being able to ‘seek assistance from their co-workers’ at similar levels ([23], p. 1). When one has support from one’s peers, good employee behavior, such as proposing improvement on their organization, can be the result [23]. Peer support is important because it fulfils the need for autonomy, competence, and relatedness. Autonomy refers to an individual working within their interest. One could also develop selling skills and take the challenge. Relatedness refers to individuals connecting to others and being cared for. Interactions with colleagues and superiors will satisfy relatedness. As a result, satisfaction leads to higher commitment and engagement [24].

Consequently, the following hypothesis is proposed:

Hypothesis 2 (H2).

Perceived support from sales colleagues (peer) is associated with work engagement.

2.5. Association between Superior Support and Work Engagement

Previous research has shown that employees can obtain better superior support when they have a good relationship with managers [25,26]. A salesperson’s motivation is positively related to sales manager support. The support enhances a salesperson’s future expectations. Future expectations include a salesperson’s level of self-esteem, a level on Maslow’s hierarchy of needs [4]. When one has good managerial support, they are more engaged in their work because they are being motivated internally. Employees feel good and their competence is enhanced. In addition, managers that make fair judgements on rewards contribute to employees’ work engagement [27] Social support from an immediate superior positively correlated with work engagement [12].

When employees customize their career or are given a choice to develop their career path, high manager support with career customization program implementation was found to be related to employees’ work engagement and affective commitment. Managers who support the career program were essential to its success [28].

Consequently, the following hypothesis is proposed:

Hypothesis 3 (H3).

Perceived support from superior associates with work engagement of salesperson.

2.6. Association between Managerial Support from other Departments and Work Engagement

Research on the mentoring system of an organization shows that newcomers have a higher commitment and job satisfaction. Mentors could provide more company information and possible psychological support to help new employees adjust to their new working environment [29]. Mentors are usually senior people from other departments who do not have a conflict of interest with their mentees.

Can the same system apply to salespeople who are not necessarily new employees?

Hypothesis 4 (H4).

Perceived managerial support from other department managers is associated with the work engagement of salespersons.

2.7. Gender

Sales team performance has been reported to improve in terms of lower turnover rate, better relational skills, and greater organizational citizenship behavior when females join an all-male sales team. A female salesperson will stay longer in a position as compared to a male salesperson. A female salesperson has more relational behaviors, such as collaboration and showing concern for colleagues. Moreover, female salespeople are more likely to engage in helping behavior and influence the other members of the sales team [30].

Salespeople often have fluctuating emotions because of their performance. Male employees are more rational. They find underlying causes and seek appropriate solutions. Female employees are more emotional, and thus, need to talk to other people. Hence, the question becomes, does gender matter in the management of salespeople? Do female salespeople need more support from peer and managers compared to male salesperson? Gender is proposed as the moderator between peer support and work engagement, manager support (own department) and work engagement, and manager support (other department) and work engagement, respectively.

Our conceptual model is shown in Figure 2.

3. Methodology

Our study consists of a focus group meeting and a survey. The focus group meeting of sales professionals was conducted for this study in October 2020. Failure experience, how to mitigate emotional problems, and how to maintain a positive selling attitude to clients were the discussion topics. Six salespeople ranging from junior sales to senior managers from international insurance/financial/retail industries were recruited. Years of sales experience ranged from 3 months to 10 years. Three of the respondents were females and the rest were males. The focus group meeting was in a semi-structured format and questions were pre-set. Respondents were asked one by one, but they were allowed to discuss freely among themselves. The whole meeting lasted for an hour and was recorded and subsequently transcribed. The main findings of the focus group were sharing selling experiences among colleagues after office hours was a usual way to reduce the negative feelings of salespeople, enabling them to resume their work the next day with almost full energy.

A cross-sectional survey was then conducted during Summer 2021 subsequently in Hong Kong. The questionnaire link was distributed to salespeople through initial contacts using electronic mail. Initial contacts were the salespeople that the researchers knew. Efforts were exerted to ensure that we reached equal portions of female and male salespeople in various industries, including automotive, banking, insurance, manufacturing and technical products. About 70% of the respondents already have more than five years of sales experience. We sent out 240 emails and received 144 responses after three reminders. The response rate was 60%. We compared the initial batch of answers with the final batch answers. No significant difference was found, and thus, the non-response error can be minimized.

Respondents had to answer two screening questions before the main section of the questionnaire. They were asked whether their sales duties occupy at least half of their working time and whether they have a clear sales target. If one of the answers was positive, their filled-in questionnaires were counted towards our pool. The main purpose of the screening questions was to ensure that the respondents are salespeople and subject to some challenges in the competitive marketplace. Finally, 140 suitably filled-in questionnaires were collected with 70 male salespeople and 70 female salespeople. All the questions were arranged in a random order to avoid common bias method error.

Participants were contacted using electronic mail. They were given study information. We obtained all the consent from the participants and they were free to exit the survey at any time. They were all adults and receive no financial reward by doing the survey. The respondents’ mean age was around 40 and they were mainly from financial industries. Most of them had an associate degree or bachelor degree and had been working for more than 5 years (

Table 1. Demographic data of respondents.

Category		Frequency	Percentage %
Gender	Male	70	50.0
	Female	70	50.0
Age	18–30	36	25.7
	31–40	30	21.4
	41–50	52	37.1
	51–60	16	11.4
	61 or above	6	4.3
Education	Secondary school or below	36	25.7
	Associate degree/higher diploma	38	27.1
	Bachelor degree	50	35.7
	Master degree or above	16	11.4
Industry	Insurance	78	55.7
	Financial services	18	12.9
	Retailing and customer services	20	14.3
	Others	24	17.2
Existing job	Less than 2 years	12	8.6
Selling exp	2 years to less than 5 years	14	10.0
	5–10 years	106	75.7
	More than 10 years	8	5.7

).

3.1. Measurement

Please refer to the Appendix A of our questionnaire items.

3.2. Work Engagement

The scale was based on the Utrecht Work Engagement Scale [31]. There are nine items. A sample item is ‘At my work, I feel bursting with energy’.

3.3. Core Self-Evaluations

The core self-evaluations scale was adapted from [32]. A sample item is ‘I am confident I get the success I deserve in life’. Respondents were asked to answer using a five-point Likert scale.

3.4. Manager Support

This scale was adapted from [33]. A sample item is ‘My (superior) does a good job of helping me develop my potential’. Respondents were asked to answer using a seven-point Likert scale.

3.5. Support from Colleagues Who Belong to the Managerial Level from Another Department

This scale was adapted from [34]. A sample item is ‘My colleagues who belong to the managerial level from another department encourage me to do the selling’. Respondents were asked to answer using a seven-point Likert scale. Alpha coefficient = 0.72.

3.6. Perceived Peer Support

This scale was adapted from [34]. The sample item is ‘My peers are interested in selling’. Respondents were asked to answer using a seven-point Likert scale. Alpha coefficient = 0.67.

4. Data Analysis

Partial Least Squares (PLS) was used for data analysis to predict and explain the variance of target constructs (for instance, ‘core self-evaluation’ in the study) by explanatory construct(s) (for instance, ‘Manager support’) in the study [35]. SmartPLS 3.0 software was used to test our model.

The PLS is more robust with fewer identification problems and can be used in small and large samples. The PLS results of the bootstrap samples provide the standard error for each path framework. According to [36], bootstrapping is a process in which statistics (referred to here as regression weights) are calculated over a huge number of repeat manipulations. The samples were drawn with the replacement method from a dataset. For instance, 5000 bootstrap samples were drawn from a given dataset in the study [36].

The main purpose of bootstrapping is to reduce the effect of random sampling errors [37]. The default setting for the most popular PLS software, SmartPLS, is 500. With the increase in computing power, the computation time is reduced to a few seconds as compared to a few minutes a decade ago. Student t-tests are used to examine the significance of path model relationships with this information [37,38]. The high statistical power of PLS means that the method is adequate for theory building that focuses on critical success drivers.

According to [35], a reflective measurement model is a model where the arrows’ direction to the indicators is from the construct, leading to the assumption that the construct itself causes the measurement of indicator variables [35]. It has been pointed out that several criteria must be reviewed for the reflective measurement model evaluation. They are indicator reliability, internal consistency reliability, and convergent validity. Standardized indicator loading should be larger or equal to 0.70, although loadings of 0.40 are acceptable in exploratory studies. Composite reliability larger than 0.70 and average variance extracted (AVE) greater than 0.50 are good [39]. As PLS uses more indicators with strong reliability, composite reliability is a good tool for establishing internal consistency compared to Cronbach’s Alpha. The Cronbach’s Alpha is regarded as the lower limit of reliability and composite reliability is the upper limit [40]. The results would be used to measure related reliability and validity in the study.

In this study, PLS is proposed to test the proposed framework because researchers expect the presence of several interaction terms and the variables collected may not be normal in their distribution. More importantly, the sample size could be more flexible in PLS. The minimum sample size requirement is ten times that of the most complex association in PLS [41]. Thus, the required sample size is 40 in PLS in this study. One way to improve the precision in the parameter estimation for reflective construct in PLS is to increase the number of indicators for a particular construct [37]. However, a tradeoff is that it makes the questionnaire longer, which could cause the respondents to be unwilling to join the survey.

According to [37], model complexity has a direct effect on the sample size requirement in SEM-CB but not necessarily in PLS. PLS can afford a more complicated model of researcher estimates provided that the basic sample size requirement is fulfilled [37]. PLS assumes data distribution of the ordinary least squares (OLS) regression concerning data properties and does not require a normal data distribution. However, bootstrapping standard error may increase due to non-normal data [40].

All the reliability and validity measures are satisfied after data cleaning. First, all variables of outer loadings of all indicators were greater than 0.70. One indicator of work engagement and one of peer support was slightly below 0.70. They were retained for completeness of the scales. Second, the Cronbach’s alphas of all constructs were greater than 0.70 (except for manager support at 0.663) with an average variance extracted (AVE) greater than 0.50. Hence, convergent validity is acceptable [42]. Finally, the discriminant validity was assessed using the Fornell–Larcker criterion (

Table 2. Measurement model.

Constructs and Items	Loadings	AVE	Composite Reliability	Cronbach’s Alpha
Self-Evaluation of Success [32]		0.577	0.912	0.756
When I try, I generally succeed.	0.750
I complete tasks successfully.	0.720
Overall, I am satisfied with myself.	0.846
I determine what happen in my life	0.716
Peer Support [34]		0.556	0.833	0.734
My peers are interested in selling.	0.686
When my peers and I get together, we enjoy doing selling.	0.763
My peers and I like to help each other with selling.	0.799
My peers and I enjoy talking about selling.	0.729
Other Manager Support [34]		0.601	0.857	0.778
My colleagues who belong to the managerial level from other departments/divisions encourage me to sell.	0.807
My colleagues who belong to managerial level from other department/division think being good at selling is useful for my future.	0.706
My colleagues who belong to managerial level from other department/division think that I can do well at selling.	0.800
My colleagues who belong to managerial level from other department/division are happy with my selling progress.	0.784
Manager Support [33]		0.596	0.815	0.663
My sales manager gives me recognition for improvement in my performance.	0.805
My sales manager demonstrates confidence in my ability to meet most objectives.	0.796
My sales manager shows approval for me when I put forth my best efforts.	0.711
Work Engagement [31]		0.599	0.912	0.888
At my work, I feel bursting with energy.	0.827
At my job, I feel strong and vigorous.	0.720
I am enthusiastic about my job.	0.831
My job inspires me.	0.757
I feel happy when I am working intensely.	0.681
I am proud of the work that I do.	0.843
I am immersed in my work.	0.742

and

Table 3. Discriminant validity.

	Other Manager Support	Peer Support	Success	Work Engagement	Manager Support
Other Manager support	0.775
Peer support	0.659	0.746
Success	0.696	0.597	0.760
Work Engagement	0.703	0.572	0.636	0.774
Manager support	0.569	0.459	0.444	0.603	0.772

).

The result of our structural model is shown in Figure 3.

The adjusted R-squared value for work engagement and self-evaluation are 0.548 and 0.396, respectively, and could be described as substantial [43]. Moreover, 54.8% of the variance in work engagement and 39.6% of the variance in self-evaluation of success can be explained by our model. Predictive relevance was checked through the blindfolding calculation. The Q-square for self-evaluation of success is 0.207 and work engagement is 0.308, which are small and medium predictive relevance, respectively [44].

Hypotheses one to seven were tested using PLS-SEM analysis. The results are summarized in

Table 4. Summary of PLS-SEM analysis.

Path	Hypothesis	Path Coefficient	T Statistics	p Values	Result
Work Engagement → Self-evaluation of Success	H1	0.636	6.385	0.000 ***	Support
Peer support → Work Engagement	H2	0.151	1.216	0.224	Not supported
Manager support → Work Engagement	H3	0.282	2.357	0.018 *	Support
Other manager support → Work Engagement	H4	0.442	3.391	0.001 **	Support

* p < 0.05; ** p < 0.01, *** p < 0.001.

. Three hypotheses are supported (H1, H3, and H4). Manager support and support from other managers were associated with work engagement. Work engagement was associated with self-evaluation of success. Peer support was not associated with work engagement.

Multi-group analysis (MGA) was conducted among two subsamples, male salespersons (n = 70) and female salespersons (n = 70), to investigate the effects of gender on the relationship among variables. Work engagement was found to be associated with self-evaluation of success irrespective of gender. Peer support was found to be not associated with work engagement for both genders. Other manager support related to work engagement of female salespersons (t = 2.771, p = 0.006) but not of male salespersons (t = 1.400, p = 0.162). Manager support could enhance the work engagement of male salespersons (t = 3.152, p = 0.002) but not female salespersons (t = 0.880, p = 0.379).

5. Discussion

Other factors also affect work engagement, including empathy, learning organization, and employee resilience [45,46]. This study investigates the internal social support from the corporation, which is more controllable from the company perspective. Our results show that the self-evaluation of success was positively correlated with work engagement, which is in line with previous studies [16,18].

These results indicate that we have to establish the self-confidence of female salespersons. Salespeople need to have the confidence to avoid frustrations. One tactic can be to use the support of a manager from another department instead of one’s manager. The effectiveness of this tactic might be because of there being less conflict between managers from other departments and the salesperson themself. They can talk freely without any hesitation. Female salespeople may prefer to relieve issues on the emotional side.

However, talking to their own superior would enable salespeople to focus on how to improve their sales turnover and sales technique. Male salespeople are more rational and eager to learn how they can improve their sales techniques. Hence, the work engagement of male salespeople can be improved by talking with their boss [4].

Peer support is not favored by our respondents, a finding which is not in line with previous studies [24]. This finding might be due to the concept of face. Salespeople do not want other salespeople to know their weaknesses. It is also possible that salespeople from the same department feel competitive with each other. As a result, the need for relatedness might not be satisfied.

6. Theoretical Contribution and Managerial Implications

The present study provides evidences of Maslow’s hierarchy of needs theory and the stimulus-organism-response theory. Corporations provide social support to sales colleagues to satisfy their needs of autonomy, competence, and relatedness, which are defined as the esteem needs in the hierarchy. Thus, salespersons are motivated to work for good performance. Hence, companies’ social support is a kind of resource that meets the job demand.

For the salespeople to maintain their confidence level, the company could consider using a mentor system to help salespeople. The mentor is usually more experienced and has high grades but are not from their mentee’s (salesperson) department. A one-to-one system would be preferable so that the privacy of the salesperson could be preserved. This system would work in particular for female salespersons. Having a high confidence level will result in a salesperson being able to recover more quickly and not be trapped in the memory of a previous failure.

7. Conclusions

Support from the senior level is important for salespeople’s work engagement. Hence, senior management must proactively meet the salespeople to see how they could facilitate the selling process being carried out.

The current paper is an innovative study on how to relieve sales pressure. However, the sample size is small and based on the insurance or financial industries mainly. A large sample size is preferred so that we could investigate whether industry matters. Our findings might not apply to other manufacturing or technical industries. Most of the respondents in this study have more than five years of experience. Hence, more junior salespeople could be recruited to compare the results with that of senior salespeople.