Examining the Relationships between Manager Monitoring Styles, Work Engagement, Job Satisfaction and Sales Performance: A Studyin the Cosmetics Industry



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Submitted Nov 28, 2024
Published Jan 20, 2025
10.24018/ejbmr.2025.10.1.2544

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To examine the distributional role of field change, observational, and interactional monitoring styles of work engagement and job satisfaction in this suitable cosmetics industry, and their relationship with the sales performance of sales personnel. A study was conducted with 293 sales personnel working at cosmetic and care product sales points in Istanbul. The study was analyzed using IBM SPSS 20.0, Process Macro v4.2, and IBM SPSS AMOS 22.0 techniques. Positive effects of work engagement on job satisfaction and interactional monitoring style, work engagement and job satisfaction on sales performance were detected (p < 0.001), but no significant effect of observational monitoring style was found on sales performance (p > 0.05). In addition, the moderate mediation roles of work engagement and job satisfaction between the interactional monitoring style and sales performance were determined. Increasing work engagement in subordinates is important in terms of both increasing job satisfaction and increasing sales. In addition, the increase in work engagement and job satisfaction of subordinates in using the communication perspective will help increase sales performance by assuming the role of an intermediary. The training of salespeople should be kept at a low level and the reinforcement weight should be increased so that managers can be trained to use interactional monitoring style more.

Keywords: Job Satisfaction monitoring sales performance work engagement

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Introduction

Cosmetics, derived from the Latin term ‘cosmos,’ means ornament and beauty (Kumar, 2005, p. 1263). Additionally, ‘kos-medicos,’ a Greek term meaning ‘master in decorating,’ is cited as the origin of the word cosmetics (Sunguret al., 2018, p. 192). According to the Cosmetic Products Regulation (2023), cosmetic products are applied to the external parts of the human body; they are mixtures prepared to be applied to the bristles, lips, hair, epidermis, and external genital organs or oral mucosa, and teeth, with the main purpose of giving scent to these parts, changing their appearance, cleaning, protecting and keeping them well. The cosmetic industry includes make-up, hair care, perfume, deodorant, toiletries, and other products (Natural Cosmetics/Dermocosmetics Sector Report, 2024). It is seen that the use of fragrance and cosmetic products dates back to ancient Egyptian, Greek, and Roman times (Kumar, 2005). The oldest known cosmetic product is soap, recorded in Sumerian records. Historically, the Egyptian pharaohs used milk, honey, and scented oils to beautify themselves; the Romans used lemon and orange for skin health, and chamomile eaters to lighten the color of their hair. The use of blush and powder became widespread in the 17th century, and lipstick and eye shadow became widespread in the 18th century (Özçelik & Bebekli, 2015).

When we look at today, the USA is the largest cosmetics market in the world, while the world’s largest exporter of cosmetic products is France. The global leader of the cosmetics industry is O’Lorèal, with a market share of 16.8%. Despite the economic crisis, the cosmetics and perfume industry in the world shows an average growth rate of 5% (Kumar, 2005). The cosmetics industry in Turkey started to develop in 1972s (Şenol, 2002). According to the Cosmetics Sector Reports of the Ministry of Health (2024), 3250 companies are registered in the electronic notification system, and a total of 14,000 people work in all departments of these companies in all provinces.

When we look at business departments in general, sales personnel and sales performance are important for businesses because the marketing department has a revenue generating feature. Because, the presence of 20% of the sales personnel plays an important role in achieving 80% of the sales performance (Greenberg & Greenberg, 1980). In order to increase the sales performance of employees, there is a need for personnel with high commitment to their work and high job satisfaction. These workers are successful in their work and view their fatigue as satisfactory (Bakker & Demerouti, 2008). Employees with job satisfaction show high performance in their jobs (Kasparkovaet al., 2018). Lyubomirskyet al. (2005) stated that happy employees use extra-role behaviors more with high performance, high production display, and safe job interviews, are less likely to engage in destructive actions such as theft and sabotage, provide better corporate management, and focus more on their work. It states that they show behaviors of attributing meaning and having a positive attitude towards other employees. From a managerial perspective, manager behaviors have positive and negative effects on employee health, performance, employee stress, and absenteeism (Gilbreath & Karimi, 2012), extra-role behavior and motivation (Schaufeli & Salanova, 2010).

This study, within the framework of Deci and Ryan’s (1985) ‘self-determination theory,’ based on Khanet al. (2020) study in the pharmaceutical industry, working in the cosmetics industry, the effect of work engagement on job satisfaction and sales performance, and the effect of monitoring styles on sales performance. It is aimed to determine the mediating roles of job satisfaction and work engagement between monitoring styles and sales performance in Turkey.

Literature Review

Self-Determination Theory

Self-determination theory is an umbrella theory created by Deci and Ryan with sub-theories related to well-being, staff development, and motivation. This theory focuses on the individual’s self-determined behavior and the cultural and social situations that create these behaviors (Ryan, 2009). This theory specifically focuses on how employees’ well-being and performance are affected by the types of motivation they have while working (Deciet al., 2017). According to this theory, there are at least three basic universal psychological needs for optimal development. These are competition, relatedness, and autonomy needs (Deci & Ryan, 2012). Individuals have to meet these basic needs because they need satisfaction. When these needs are met, the individual enjoys the actions he takes, his participation in the actions increases, and he can control his own behavior by complying with social situations (Tatli, 2019). Ryanet al. (2008) state that intrinsic motivators (e.g., playing sports, participating in a group, personal development) are more effective than extrinsic motivators (e.g., fame, wealth, image) in terms of well-being and healthy development and support the satisfaction of psychological needs more.

Observational Monitoring Style

Observational monitoring is the collection of information by managers to obtain the work process and work output performed by their subordinates, and it is a form of top-down monitoring regarding when the employee works and how he works. In this monitoring style of behavior, managers closely examine the behavior of employees, and the manager walks around among employees in the workplace. Managers examine their staff when there is a problem or in unexpected situations. This style of monitoring involves limitations in collecting information because it does not involve communication with the employee and the employee can not present his ideas to the manager (Liao & Chun, 2016). This monitoring style is used by transactional leaders to evaluate and reward employees’ contributions (Wu & Wang, 2020). Employees perceive this style of monitoring negatively because they are not involved in decision-making processes and cannot express their opinions (Hassanet al., 2018). In this style of monitoring, trust in the leader is low and has a negative impact on the creativity of employees (Hassanet al., 2018). In particular, the observational style of supervision is linked to anxiety, high stress, decreased satisfaction, low intrinsic motivation, low level of trust, and low organizational commitment (Wu & Wang, 2020). Managers do not show interest in subordinates and do not care about their development (Mishra & Ghosh, 2020).

Interactional Monitoring Style

Interactional monitoring is a style of monitoring that covers the expectations, opinions, ideas, and feedback of employees regarding work orders and processes, and in which managers try to collect information by meeting with employees or holding different types of interactions. In this style of monitoring, employees can express their suggestions, dissatisfaction, and opinions (Liao & Chun, 2016). For this reason, this monitoring style is perceived as positive by employees, and this supervision style is used by transformational leaders (Wu & Wang, 2020). Leaders provide feedback and support to their employees like a mentor (Ottoet al., 2021).

In the interactional monitoring style, managers leave employees partially free because they do not follow the work process. Subordinates and managers have regular meetings together, and the necessary resources are allocated for this. Managers help their employees in solving their problems, and the reliability of employees is taken into account in management activities and written rules of management (Wu & Wang, 2020). As employees become more involved in the work process, they will want to find creative solutions to problems (Hassanet al., 2018). The interactional monitoring style is the employees’ favorite management style. Because in this style of monitoring, the opportunity to point out poor performance and errors provides the opportunity to strengthen the quality of the manager-employee relationship (Khanet al., 2020).

Work Engagement

The term work engagement is a popular topic academically and in businesses, and it was first mentioned by the management consultancy company Gallup in the 1980s (Schaufeli & Rahmadani, 2022). The word passion was academically published by Kahn in the Academy of Management Journal in 1990 (Jindal, 2017) and defines employees who are passionate about work as individuals who devote themselves to their jobs mentally, physically, and emotionally throughout the work process. Thus, the unity of mental, physical, and emotional states emerged in the concept of work engagement (Schaufeli & Rahmadani, 2022).

It is a positive and pleasing psychological state defined by passion for work, dedication to work, energeticness, and concentration (Schaufeliet al., 2002, p. 74). Dedication; feeling of self-esteem, and strong participation in work. Energetic; It is high energy, not giving up easily, facing difficulties, and the willingness to work. Concentration; it means spending time quickly and staying at work for a long time with satisfaction (Wefald & Downey, 2009, p. 93). As seen in work engagement, it is thought to include the basic dimensions of intrinsic motivation, and these dimensions help individuals increase goal orientation, high levels of energy, and creative work behaviors (Salanova & Schaufeli, 2008).

Work engagement is a state in which a generally felt, continuous, mental, and emotional state continues, without focusing on a specific situation or time. Employees with high levels of work engagement create their own resources positively and show high performance in their jobs. The presence of employees who are passionate about their work also benefits the business and provides a competitive advantage to the organization (Abdullahet al., 2021). Individuals who are passionate about work have a feeling of satisfaction and happiness, are interested in their work, and experience the opposite of burnout, and derive a significant part of their energy from their work (Bakkeret al., 2011; Gast, 2012). They develop strong relationships, tend to be honest, and are indispensable personnel of the organizations they work in (Baklaieva, 2016; Cropanzano & Mitchell, 2005). High profitability, high production quantity, high customer satisfaction, less absenteeism, low number of work accidents, and quality problems for organizations are also revealed by the Gallup survey study (Kodden, 2020). For example, it is estimated that engaged employees save businesses in the United States from losses of $300 billion each year (Stromet al., 2014). Conversely, for employees with low levels of work engagement, a low level of organizational commitment and increased intention to quit are observed (Baklaieva, 2016). It is estimated that the cost of employees who are not passionate about their jobs to businesses is 64.8 billion dollars in the UK and 232 billion dollars in Japan (Keçecioğlu & Yilmaz, 2018).

Job Satisfaction

According to the Turkish Language Institution (2024), the term satisfaction means reaching heart satisfaction and making something desired happen. Job satisfaction is the emotional satisfaction gained by the employee at the level of meeting his job-related expectations in line with his perceptions, experiences, and knowledge (Yorulmaz & Karabacak, 2020). The concept of job satisfaction derives from the Latin word ‘satis (sufficient)’ (Bakan, 2020, p. 61) and has been widely studied in different disciplines over the last forty years (Currivan, 1999; Gazioglu & Tansel, 2006). Hoppock (1935) was the first to define the concept of job satisfaction. In this definition, it is the combination of psychological, physiological, and environmental conditions that lead the individual to say “I am generally satisfied with my job” (Boz & Alan, 2021, p. 257). The first experimental studies on this concept were the studies carried out by Mayo and his friends in the Hawthorne factory of the Western Electric Company in the early 1930s, which revealed the concept of ‘social human’ (Dawis & Lofquist, 1981, p. 3).

High job satisfaction shows that employees feel good emotionally and mentally. Employees who feel good about themselves also attach importance to customer satisfaction, work harder, their desire to stay at work increases (Aziri, 2011), and employees are more productive, creative, and happy (Somuncuoğlu, 2013). Job satisfaction also has the benefits of increased commitment to the organization, developing a greater sense of participation in management, easy adaptation to new management rules and technologies, better understanding of the reasons for management actions, reduction in waste and losses, improvement in knowledge level and productivity, and providing employees with a sense of belonging to the organization (Kumari & Rachna, 2011). Low job satisfaction creates increased discipline problems, hidden work slowdowns, low productivity, and low job performance (Akinci, 2002). It also causes insomnia, emotional depression (Kök, 2006), loss of appetite, frustration, stress, ignoring the problem, loyalty problems, high absenteeism, and turnover problems (Çekmecelioğlu, 2005). As job satisfaction increases, its reflections on the institution also become positive. For this reason, business management must offer a problem-free and rewarding business life to employees (Sevimli & İşcan, 2005). Businesses should attach importance to a human resource management that gives importance to the development of their employees and should be able to respond to employees’ complaints in order to maintain their job satisfaction (Maimako & Bambale, 2016).

Sales Performance

Sales; these are activities for which buyers and sellers pay in return for goods and services (Tosun, 2012). Sales in general; It is the process in which the seller understands the problems and needs of the buyer and introduces the product that will solve these problems and needs (Okumuşet al., 2024). Sales performance is the knowledge that sales personnel have acquired about competition, customer needs, and business products, and their perceptions of the quality of sales volume and customer relations (Krishnanet al., 2002). It refers to the actions of sales personnel that are related to sales performance, success, and organizational goals (Mackenzieet al., 1993). In order to increase sales performance, the number of sales personnel in retail outlets is increasing day by day. According to Bureau of Labor Statistics (1997), while the number of people working in marketing and sales jobs in the USA was 13,900,000 in 1992, this number is expected to increase by 18% in 2005 (Vinchuret al., 1998). The number of sales representatives is expected to reach 1.5 million in the USA by mid-2021 (Number of Employed Sales People in the United States in 2021, 2023). Increasing employee numbers indicates the importance of sales work.

Sales performance is divided into two parts in the literature: behavior and output. Output performance; It is based on objective measurements such as points, profit margin, and revenue. Behavioral performance is subjective; It is about observing various practices and skills, such as teamwork, making sales calls, sales support actions, and problem-solving. Both types of performance are important in sales performance measurement (Mallin & Ragland, 2017). Qualitative (attitude, product knowledge, creativity, decision, motivation, etc.) and quantitative measurement methods (sales volume, sales growth, sales quota, number of orders, number of lost accounts, etc.) are used in sales performance measurement (Bitmiş, 2008; Haweset al., 1995). However, today the most preferred criterion is the achievement rates of turnover or profitability targets (Tosun, 2012). Performance evaluation is generally carried out once or twice a year and provides important information to managers (Bitmiş, 2008).

Conceptual Research Framework

Monitoring is a pattern of control behavior and communication style that expresses itself between managers and employees. Managerial monitoring is; they are manager behaviors that collect information about employee behavior and work processes (Liao & Chun, 2016; Mishra & Ghosh, 2020). Since monitoring styles are new in the literature, there are not many studies. However, in Liao and Chun’s (2016) study with 385 employees, it was determined that monitoring styles were linked to trust or distrust in the manager. Researchers state that interactional monitoring can positively affect the performance of subordinates, while observational monitoring may decrease performance and increase negative attitudes (Liao & Chun, 2016). However, Khanet al. (2020) in their study with 318 salespeople found that interactional and observational monitoring styles positively affected job performance. Therefore, in this study, the relationship between monitoring styles and sales performance will be examined with the following hypotheses: H1: Managers’ interactional monitoring style has a positive and significant effect on sales performance. H2: Managers’ observational monitoring style has a positive impact on sales performance.

When the relationship between work engagement and job satisfaction is examined, it can be seen that there are many studies in the literature. In the study conducted by Okumuşet al. (2022) with hospital employees, it was concluded that job satisfaction and career satisfaction increased with the increase in work engagement and focus ability in employees. In the study conducted by Bekiroğlu and Yildirim (2021) in a textile company, it was concluded that passion for work affects job satisfaction. In Gülbahar’s (2022) study with teachers, it was found that the highest relationship was between teachers’ perceptions of job satisfaction and job engagement. In the study conducted by Arslan and Demir (2017), it was determined that there was a positive and significant relationship between work engagement and job satisfaction. Therefore, in this study, the relationship between work engagement and job satisfaction will be examined with the following hypothesis: H3: Work engagement has a positive effect on job satisfaction.

A high sales performance can be achieved with employees who are passionate about their jobs. There are studies in the literature on the relationship between work engagement and performance. For example; in the study conducted by Dinç Elmaliet al. (2021), it was determined that work engagement played a partial mediating role on the high job performance of employees. In Ersin’s (2021) research with healthcare professionals, it was determined that work engagement was effective on job performance. In the study conducted by Gümüş and Gönül (2022) with employees working in the youth and sports directorate, a positive relationship was found between work engagement and job performance. In the study conducted by İlgün Kamanli (2015), it was determined that all two sub-dimensions of work engagement, harmonious passion and obsessive passion, were positively related to employee performance. Therefore, in this study, the relationship between work engagement and sales performance will be examined with the following hypothesis: H4: Work engagement has a positive impact on sales performance.

It is thought that employees’ high levels of positive emotions about their jobs will have an increasing effect on their sales performance. In Mengüç’s (1996) study, it was determined that sales performance positively affected job satisfaction. In Akman’s (2018) study with white-collar workers, it was determined that as employees’ job satisfaction increased, their job performance and career satisfaction increased, and their intention to leave the job decreased. In Öztürk and Aygün’s (2020) study with bank employees, it was seen that job satisfaction had an impact on performance. In Yazicioğlu’s (2010) study with teachers in Turkey and Kazakhstan, a significant relationship was found between job satisfaction and performance. Therefore, in this study, the relationship between work engagement and sales performance will be examined with the following hypothesis: H5: Job satisfaction has a positive effect on sales performance.

In the study, the relationships between dual conceptual structures are revealed with various research examples. In addition, since the concepts of work engagement and job satisfaction are intrinsic motivation elements, these concepts generally play a mediating role in the studies conducted. For this reason, the following hypotheses will be examined in order to determine whether intrinsic motivation elements are effective in increasing performance in the relationship between monitoring styles and sales performance: H6: Work engagement has a mediating role in the effect of managers’ interactional monitoring style on sales performance. H7: Work engagement has a mediating role in the effect of managers’ observational monitoring style on sales performance. H8: Job satisfaction has a mediating role in the effect of managers’ interactional monitoring style on sales performance. H9: Job satisfaction has a mediating role in the effect of managers’ observational monitoring style on sales performance.

Methodology

Operationalization of Constructs

The five latent variables are measured through thirty-nine items on a five-point Likert scale from adapted measures. Observational and interactional monitoring styles are assessed on a previously developed and validated scale (Liao & Chun, 2016); observational monitoring contains five items, and interactional monitoring contains five items. The work engagement scale was developed by Schaufeliet al. (2002), and it was adapted into Turkish by Turgut (2011) and included in the research. The scale consists of seventeen items. The job satisfaction scale was developed by Brayfield and Rothe (1951). A short form was created by Judgeet al. (1998) and adapted into Turkish by Keser and Bilir (2019). The scale contains two reverse items, making a total of five items. Statements regarding the sales performance scale were prepared by Behrman and Perreault (1984) and Sujanet al. (1994). These measurement tools were compiled and translated into Turkish by Akhanet al. (2020). The scale consists of seven items. All scales were prepared as a five-point Likert type. Likert-type scale ranging from (1): ‘strongly disagree’ to (5): ‘strongly agree.’ The research model is shown in Fig. 1.

Fig. 1. The research model.

Sample and Data Collection

In this study, 600 surveys were distributed face-to-face and online to sales personnel at cosmetic sales points in Istanbul, and 333 surveys were reached. 293 surveys were valid and included in the evaluation.

Data Analysis and Results

Descriptive Statistics

The frequency and percentage distributions regarding the basic characteristics of the volunteer participants who participated in the study are shown in Table I.

Demographic features Frequency Percentage
Gender Woman 242 82.6
Man 51 17.4
Total 293 100.0
Age 24 years and under 170 58.0
25–40 age range 86 29.4
41–54 age range 28 9.6
55 years and above 9 3.1
Total 293 100.0
Marital status Married 78 26.6
Single 215 73.4
Total 293 100.0
Education status Primary school 36 12.3
High school 150 51.2
Associate degree 60 20.5
Bachelor’s degree 45 15.4
Postgraduate education 2 0.7
Total 293 100.0
Total working time in sales area Less than 1 year 83 28.3
1–3 years range 75 25.6
4–6 years range 63 21.5
7–9 years range 33 11.3
10 years and above 39 13.3
Total 293 100.0
Performance bonus system whether it works with I work 264 90.1
I do not work 29 9.9
Total 293 100.0
Table I. Frequency and Percentage Distributions of Sample Characteristics

Exploratory Factor Analysis

Varimax orthogonal rotation was used in the analysis of the research. Cronbach’s alpha values were examined to test the reliability of the scales. As seen in Table II, the scales were found to be reliable measurement tools. Because Cronbach alpha value of 0.80 and above shows that the scales are highly reliable (Arslantürk & Arslantürk, 2016).

Scale name Factors Alpha
Items 1 2 3 4 5 6 7
 Sales performance Item 33 0.809 0.901
Item 35 0.805
Item 38 0.779
Item 34 0.770
Item 36 0.743
Item 37 0.707
Item 39 0.700
Total explained variance: 12.539; KMO Test: 0.925; Bartlett: 1073.462 df: 21; p: 0.000
Observational monitoring Item 1 0.876 0.905
Item 2 0.839
Item 3 0.838
Item 4 0.822
Item 5 0.759
Total explained variance: 23.042; KMO Test: 0.879; Bartlett: 911.90; df: 10 p: 0.000
Interactional monitoring Item 6 0.870 0.908
Item 10 0.842
Item 8 0.828
Item 7 0.813
Item 9 0.778
Total explained variance: 33.421; KMO Test: 0.891; Barlett: 927.626 df: 10 p: 0.000
 Work engagement Item 20 0.731 0.911
Item 17 0.715
Item 19 0.688
Item 21 0.668
Item 22 0.655
Item 18 0.646
Item 26 0.779
Item 23 0.749
Item 25 0.745
Item 27 0.705
Item 24 0.699
Item 15 0.709
Item 13 0.619
Item 14 0.583
Item 11 0.572
Item 16 0.562
Item 12 0.547
Item 20–18 range: Concentration; Item. 26–24 range: Dedication; Item 15–12 range: Energetic dimension
Total explained variance: 60.432; KMO Testi: 0.914; Barlett: 2483.708 df:136; p: 0.000
 Job satisfaction Item 31 0.813 0.835
Item 28 0.715
Item 29 0.697
Total explained variance: 66.957; KMO Test: 0.710; Barlett: 351.984; df: 3; p: 0.000
Table II. Transformed Components Matrix

After correcting the scores of these items on the job satisfaction scale, which were included in reverse scoring such as “Item 30: Every day at work feels like it will never end’“ and “Item 32: I think my job is unpleasant,” it was seen in the transformed factor matrix that it was included as the 8th factor in the factor analysis. The fact that the scale was created as a single-factor short form means that Anderson and Rubin (1956) and Stevens (2009) stated that it is not appropriate to call factors containing fewer than three items in a factor as ‘factors,’ because as the number of items decreases, the items appear as factors. These two items were removed from the analysis because they stated that they would be released.

Validity and Reliability Analysis

Item-total score correlations were examined in line with the desired feature measurement level of the items in the scales. An item-total correlation value of >0.30 indicates that the statement is valid (Karaman, 2023). It is seen that the expressions in the scales measure the desired feature, as seen in Table III. According to the results of the confirmatory factor analysis in this study, AVE and CR values are determined to have sufficient validity by providing the relevant conditions. As seen in Table IV, it is seen that the relationships between the constructs are less than 1, the square root of the AVE values is greater than 0.50, and the conditions are greater than the largest correlation value between the constructs.

Factors Item-total score correlation range λ α AVE CR
Sales performance 0.648–0.809 0.70–0.809 0.901 0.578 0.905
Observational monitoring 0.724–0.853 0.759–0.876 0.905 0.685 0.916
Interactional monitoring 0.697–0.840 0.778–0.870 0.908 0.684 0.915
Work engagement 0.389–0.773 0.547–0.779 0.911 0.452 0.932
Concentration 0.522–0.740 0.646–0.731 0.835 0.468 0.841
Dedication 0.637–0.762 0.699–0.779 0.870 0.542 0.855
Energetic 0.547–0.805 0.547–0.749 0.858 0.361 0.771
Job satisfaction 0.666–0.752 0.697–0.813 0.835 0.553 0.787
Table III. Validity and Reliability Results
Variables SP OM IM WE JS
SP (0.760)
OM −0.047 (0.827)
IM 0.299** −0.345** (0.827)
WE 0.459** −0.365** 0.368** (0.672)
JS 0.328** −0.296** 0.175** 0.604** (0.743)
Table IV. Inter-Variable Correlation Analysis Results

Confirmatory Factor Analysis

In this study, confirmatory factor analysis was used to test the measurement model. It is seen that the path coefficients in the measurement model and all variables in the measurement model are significant at the p < 0.001 value level, and the standardized analysis results are presented in Fig. 2.

Fig. 2. Measurement model compatibility (Standardized). Note: SP = Sales Performance, OM = Observational Monitoring, JS = Job Satisfaction, IM = Interactional Monitoring, WE = Work Engagement.

When the measurement model fit indices are examined; The X2/df value was found to be 2.264, which is at an acceptable level of fit since it provides 2 ≤ X2/df ≤ 5. The PRatio value was found to be 0.929, which is at a perfect fit level between 0–1. The TLI value was found to be 0.863, which is at an acceptable level of fit between 0.80 and 0.95. The RMSEA value was found to be 0.066, which is at an acceptable level of fit within the range of 0.05–0.08. The PNFI value was found to be 0.738, which is at an acceptable level of compliance within the range of 0.50 ≤ PNFI ≤ 0.95.

Structural Equation Model Analyzes

Structural model analyses of the hypotheses stated in Table V were conducted. Structural equation model (SEM) H1, H3, H4, and H5 hypotheses path coefficients were found to be statistically significant at the 0.001 level. It was observed that interactional monitoring in the H1 hypothesis explained the sales performance level by 11.3% (R2: 0.113), while work engagement in the H3 hypothesis explained the job satisfaction level by 71.8% (R2: 0.718). It was observed that work engagement in the H4 hypothesis affects the sales performance level by 28.3% (R2: 0.283), while job satisfaction in the H5 hypothesis explains the sales performance level by 15.7% (R2: 0.157). SEM H2 hypothesis path coefficient was not found to be statistically significant and H2 hypothesis was rejected (H2-β1: −0,086; p < 0,05).

H Path coefficient β1 β2 S.E. C.R. R2 p Acceptance/Rejection
H1 0.34 0.337 0.243 0.045 5.393 0.113 *** Accepted
H2 −0.09 −0.086 −0.052 0.039 −1.343 0.007 0.179** Rejected
H3 0.72 0.718 0.724 0.077 9.348 0.718 *** Accepted
H4 0.53 0.532 0.589 0.072 8.163 0.283 *** Accepted
H5 0.40 0.396 0.387 0.065 5.964 0.157 *** Accepted
Table V. SEM Hypothesis Results

Mediation Analyzes

In this study, analysis was conducted using the Process Macro analysis Model 4, using 5000 samples with a bootstrap confidence interval of 95%.

According to the mediation analysis shown in Fig. 3, interactional monitoring positively affects (a path) work engagement (F: 45.486, p < 0.001; β: 0.241, %95 CI (0.171; 0.311), t: 6.744, p < 0.001). The R2 value is 0.135, indicating that 13.5% of work engagement is explained by interactional monitoring. It was determined that work engagement significantly (b path) affected sales performance (β: 0.474, 95% CI (0.346; 0.602), t: 7.292, p < 0.001). It was found that interactional monitoring significantly affected sales performance (path c) (β: 0.116, 95% CI (0.032; 0.200), t: 2.722, p: 0.007). It is understood that the unstandardized beta value is significant due to both the p values and the confidence intervals not containing zero values. Additionally, work engagement and interactional monitoring explain 23.1% (R2: 0.231) of sales performance. When the total effect (c’ path) is examined, there is no work engagement, which is the mediator variable, but interactional monitoring affects sales performance; total effects were found to be significant (β: 0.230, 95% CI (0.146; 0.315), t: 5.351, p < 0.001). The R2 value is 0.090, and it was determined that interactional monitoring explained 9% of sales performance.

Fig. 3. The mediating role of work engagement in the relationship between interactional monitoring and sales performance.

If the mediator variable, work engagement, was included in the model, the calculated indirect effects were found to be significant (β: 0.114, 95% BCA CI (0.066; 0.175). Because indirect effects’ confidence interval values do not include the zero value. The full standardized effect size (K2) of the mediation effect is 0.149, and it can be said to have a medium level. Hypothesis H6 is supported with a moderate level of mediation.

In the mediation analysis, firstly, a regression analysis is conducted between the independent variable (observational monitoring) and the dependent variable (sales performance), and then the independent variable (observational monitoring) and the variable that is thought to have a mediating effect (work engagement/job satisfaction) are examined to determine whether the resulting relationships are significant. Finally, a regression analysis should be performed in which the mediator variable (work engagement) and the dependent variable (sales performance) are controlled, and in the second stage, it should be checked whether the effect of the independent variable on the dependent variable has completely disappeared. In this part, the effect decreases, but if the relationship is significant, the partial mediation effect continues to exist. If the effect in the first stage disappears, a full mediation effect is mentioned (Şahin & Yilmaz, 2020).

In the H2 hypothesis (stage I), it was seen that observational surveillance did not have a valid effect on sales performance at the p < 0.05 significance level, and since the first stage could not be completed, H7 and H9 hypotheses were rejected due to the mediation analysis condition not being met (H2; β1: −0.086; C.R.: −1.343).

According to the mediation analysis shown in Fig. 4, interactional supervision positively affects job satisfaction (a path) (F: 9.169, p: 0.003; β: 0.155, 95% CI (0.054; 0.255), t: 3.028). The R2 value is 0.031, indicating that 3.1% of job satisfaction is explained by interactional monitoring. It was determined that job satisfaction significantly (b path) affects sales performance (β: 0.247, 95% CI (0.154; 0.340), t: 5.218, p < 0.001). It was found that interactional monitoring significantly affected sales performance (c path) (β: 0.192, 95% CI (0.110; 0.274), t: 4.589, p: 0.000). It is understood that the unstandardized beta value is significant due to both the p values and the confidence intervals not containing zero values. Additionally, job satisfaction and interactional monitoring explain 16.8% (R2: 0.168) of sales performance. When the total effect (c’ path) is examined, there is no job satisfaction, which is the mediator variable, but interactional monitoring affects sales performance; total effects were found to be significant (β: 0.230, 95% CI (0.146; 0.315), t: 5.351, p < 0.001). The R2 value is 0.090, and it was determined that interactional monitoring explained 9% of sales performance.

Fig. 4. The mediating role of job satisfaction in the relationship between interactional monitoring and sales performance.

If the mediator variable, job satisfaction, was included in the model, the calculated indirect effects were found to be significant (β: 0.038, 95% BCA CI (0.009; 0.077). Because indirect effects’ confidence interval values do not include the zero value. The full standardized effect size (K2) of the mediation effect is 0.05, and since it is close to 0.09, it can be said to have a medium level mediation effect. Hypothesis H8 is supported with a moderate mediation effect.

Discussion and Conclusion

In this study, a research model was developed and analyzed by considering the relationships between manager monitoring styles, sales performance, work engagement, and job satisfaction.

In the hypothesis tests, the positive effect of managers’ interactional monitoring style on sales performance was determined, and the H1 hypothesis was accepted. However, the effect of managers’ observational monitoring style on sales performance could not be determined. With the rejection of the H2 hypothesis, the mediation hypotheses H7 and H9 were also rejected. The rejection of hypothesis H2 shows that the studies of Komaki (1986) and Liao and Chun (2016) support the fact that observational monitoring does not affect sales performance. Additionally, the studies of Komaki (1986), Liao and Chun (2016), and Khanet al. (2020) appear to have similar results regarding the positivity of the interactional supervision and performance relationship. The positive effect of work engagement on job satisfaction was determined, and the H3 hypothesis was accepted. It is seen that the result of this study is similar to the studies of Thokoaet al. (2021), Okumuşet al. (2022), Orgambidez-Ramos and de Almeida (2017), Şahin and Çankir (2019). The positive effect of work engagement on sales performance was determined, and the H4 hypothesis was accepted. No study has been found in the literature on the relationship between sales performance and work engagement. However, this study showed similar results between work engagement and performance (employee performance, organizational performance, etc.) as reported by Al-dalahmehet al. (2018), Wang and Chen (2020), Silitongaet al. (2017), and Ersin (2021). The positive effect of job satisfaction on sales performance was determined, and the H5 hypothesis was accepted. It is seen that the hypothesis result is compatible with the studies of Tekingündüzet al. (2015), Akman (2018) and Öztürk and Aygün (2020). Considering the mediation analyses, the H6 hypothesis was accepted by determining the moderate mediating role of work engagement in the relationship between interactional monitoring and sales performance. In determining the moderate mediating role of job satisfaction in the relationship between interactional monitoring and sales performance, the H8 hypothesis was accepted.

The interactional monitoring style had a positive effect on sales performance, while the observational monitoring style had no effect on sales performance. In this sense, it is important for managers to have a more effective working relationship with their subordinates. It has been determined that work engagement has an impact on job satisfaction, and the concepts of work engagement and job satisfaction also have an impact on sales performance. In this case, increasing the level of work engagement in subordinates is important in terms of both increasing job satisfaction and sales performance. In addition, the increase in employees’ work engagement and job satisfaction levels when using the interactional monitoring style plays a mediating role and increases sales performance.

Businesses should examine the monitoring styles their managers use and train their managers to use the interactional monitoring style more. In order to increase the level of work engagement and job satisfaction of employees, various human resources practices and training should be implemented, and an organizational environment that will be accepted by all employees should be provided. By giving importance to the marketing unit, the training of sales personnel should be given priority, and the immediate superiors of these personnel should be given effective leadership styles and various trainings.

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