Academy of Accounting and Financial Studies Journal (Print ISSN: 1096-3685; Online ISSN: 1528-2635)

Review Article: 2022 Vol: 26 Issue: 5

Impacts of Corporate Social Responsibility to Corporate Financial Performance: A Case Study of Vietnamese Commercial Banks

Quang Van Ngo, Hanoi University of Industry

Huyen Nguyen Thi Thu, Hanoi University of Industry

Citation Information: Ngo, Q.V., & Thu, H.N.T. (2022). Impacts of corporate social responsibility to corporate financial performance: a case study of vietnamese commercial banks. Academy of Accounting and Financial Studies Journal, 26(5), 1-14.

Abstract

The study examines factors in personal selling that affect customer satisfaction in the chemical industry. Specifically, research attempts to prove customer care, personal connections between sellers and buyers, product knowledge, and competence of salespeople are factors in personal selling that affect customer satisfaction by designing questionnaires and randomly sending them to customers who buy chemical products. The study obtained 277 answers encoded and cleaned using SPSS software, following a process of cleaning and coding conducting reliability testing, discovery factor analysis, correlation, and multi-variable regression analysis. The results showed that there are four determinant factors that influence customer satisfaction in personal selling with the case of chemical industry in Vietnam, namely, customer care, personal connection, product knowledge and employee competence. In which, employee competence contributes as the most important factor and these factors explain of 60.6% of customer satisfaction. This study also discussed about the theoretical and practical contribution of this research, as well as the limitation and future research direction.

Keywords

Customer Satisfaction, Customer Care, Personal Connection, Product Knowledge, Employee Competence, Personal Selling.

Introduction

The most crucial goals in a company are always profitability and sales performance. Currently, maintaining a competitive advantage for product and service quality are other aspects to consider in order satisfying more demanding customers. In particular, customers in the B2B market, have higher expectations of their sellers. To maintain a competitive advantage, today's sellers must ensure their sales performance while also providing clients with a service that meets their growing needs.

Chemicals is one of the fundamental industries, it exists in all nations and has a long history, contributing significantly to most activities of the industrial production process in particular and to the social economy in general. For the Vietnam, the chemical industry has become a household name. Chemicals are found in all industries, from the manufacturing phases in factories to the food and food production process. Economists point out that as the socioeconomic landscape evolves and new businesses arise, the need for chemicals grows larger and more diverse.

The Chemicals industry is placed 5th in terms of size in the manufacturing sector's ranking of industries for its direct annual contribution to GDP. The chemical industry contributes to 8.3 percent of the worldwide manufacturing sector's overall economic value. Despite its significant economic contribution, the chemical industry has had numerous negative effects on the living environment as a result of mining and industrial activities. As a result, rigorous rules exist in certain industrialized countries throughout the world, slowing the progress of this industry and driving many enterprises to look for new markets, including Vietnam. This is seen as an opportunity for Vietnam to continue its technological advancements with more advanced manufacturing techniques, as well as a challenge for native businesses. Chemical businesses with foreign investment have substantial economic and technological resources when they are founded. The majority of businesses in this industry in Vietnam are small and medium-sized, and they face tough competition from FDI businesses.

Chemicals are a unique commodity; hence the majority of consumers for firms in this field are businesses. The number of institutional customers is usually lower than the number of individual customers, but the volume of items they buy at a time is often much bigger, and they also purchase much more frequently than individual customers. The level of customer focus as an organization is also much higher. On the other hand, the client's requirement as an organization is valued higher than individual consumer requirements.

Customer requirements are usually an issue that the company pays close attention to particularly in B2B sales. It's critical since B2B sales usually have large order values, a longer sales cycle, and a more complicated process than B2C sales. According to some studies, up to 82 percent of industrial manufacturers believe their customers have high or very high expectations, and corporate customers are frequently dissatisfied with the products they receive, and they are constantly looking for new products and new suppliers to replace old ones (Lynch et al., 2016).

There has been a lot of research into customer satisfaction with individual sales in the future. Customer satisfaction with salesman is determined by aspects such as your ability to negotiate, presentation, and service offered by a salesperson, as well as knowledge, skills, and salesperson form. Customers who appreciate salespeople are more satisfied, according to this study, which also highlights the value of personal sales in helping firms attain customer satisfaction (Singh et al., 2019).

Individual sales, according to Banerjee (2013) improve product progression and are the most effective advertising-specific mechanism for companies to make their clients happy and expand their customer base (Banerjee, 2013). Furthermore, according to Moghareh Abed & Haghighi (2016), personal selling techniques such as supervised selling, multi-selling and traditional techniques contribute to strong and long-lasting relationships with clients in UK institutions (Moghareh Abed & Haghighi, 2016). Besides et al. (2014) argue that personal selling encourages creative agreements and improves the image of the organization which is good for customers and remains most applicable and is an achievement factor essential in the exhibits in the Philippines (Ocon & Alvarez, 2014). In Kenya, Cheserem (2016) found that the role of personal selling is not only focused on satisfying preferences by providing products, but also on stimulating inquiries through data, creating closeness and customer satisfaction (Cheserem, 2016). Adesoga (2016) investigated the impact of specific transactions on sales and found that personal selling affects sale (Adesoga, 2016). Mbugua (2014) investigated the personal selling methods and practices of pharmaceutical companies in Nairobi and found that the organizations were using their sales processes to advertise and market their products, this has had a positive effect as customers get to meet their requirements in a better way (Mbugua, 2014). Today, sales are still considered suitable for production and business organizations, how to satisfy buyers' requirements is still a great formula for sellers. The perceived value that customers receive is a factor that has a great influence on the buyer's decision (?en Küpeli & Özer, 2020). A customer will feel satisfied if they feel the perceived value they receive is greater than the cost of purchase (Dennis et al., 2020).

In order to be able to better define the effectiveness of personal selling, there have been many studies conducted to determine the factors in personal selling that bring satisfaction to customers. Some studies can be mentioned such as: Studies on how strategies used in personal selling affect customer satisfaction (Mbugua, 2014, Moghareh Abed & Haghighi, 2016, Kwak et al., 2019). Mbugua mentioned that the sales strategy in personal selling is the method of reaching customers that bring them maximum satisfaction in order to attract more and more customers and give them an edge over the competition improve organizational performance (Mbugua, 2014). High performing organizations are those that can retain existing customers and attract new ones, improving customer satisfaction is a sustainable approach (Jumaev & Hanaysha, 2012). In a customer research, personal selling strategy is defined as the method of persuading customers to use the company's products and services by discovering customers' needs and providing them with the optimal solution to satisfy that need (Ayimey et al., 2013). Besides, a number of studies demonstrate that the quality of personal selling services provided by the company is an important factor affecting customer satisfaction (Adesoga, 2016). Or some studies on factors in personal selling affecting customer satisfaction refer to cultural factors (Yan & Berliner, 2013), Yan and Berliner prove that differences and similarities in culture in the personal selling process had an influence on customer satisfaction in their study. As can be seen, the above studies focus on other factors of personal selling more than the relationship between the seller and the buyer.

In an era of fierce competition between many domestic and foreign businesses and companies, personal selling is becoming more important than ever. Personal selling is an opportunity for the company to convey information about the products and services that the company provides, and it is also an opportunity for the company to convince customers to use the product of the company. If salespeople do not perform well at this stage, they have missed the opportunity to interact directly with customers to convince them to buy. Moreover, If the salesman's sales skills are not good, the employee does not clearly understand the features, uses and values that the company's products bring to customers, the process of persuading customers to buy the company's products will be difficult. In the context of Vietnam's chemical market, domestic enterprises face stiff competition from themselves and foreign-invested corporations with strong financial and strategic resources. To fill the above gap, this study focuses on the relationship between seller and buyer in personal selling, which can include factors such as customer care, personal connection, product knowledge, employee competence. This study attempts to answer the following questions:

1. First, what factors in personal selling that affect customer satisfaction?
2. Second, the influence of factors in personal selling on customer satisfaction?

Theoretical Basis and The Dwvelopment of Hypotheses

Control Theory

To clarify the influence of factors in personal selling that influence customer satisfaction this study uses control theory. Control Theory Carver & Scheier (1982) provides a scale that helps clarify the ingenuity of servicers because this theory is closely related to the contradiction of simultaneously pursuing goals such as sales performance.

Some studies have used this theory to clarify the problem they are studying. Harris et al., (2005) demonstrate that control theory helps them explain the impact of goals on the relationship and communication of consultants with their clients (Harris et al., 2005).

The standard of evaluation or sales performance may vary depending on different circumstances such as the manager's navigation or the customer's desire. Control theory also proposes that we should prioritize goals according to their importance. Therefore, decentralization of the target system and orientation of the activities of the implementation of the set objectives is necessary activities. Control theory also provides a system of reasoning that helps sellers allocate resources rationally to achieve opposing goals such as customer satisfaction, and sales performance. Therefore, this theory is used to answer our research questions related to these behaviors.

Customer Satisfaction

The basic premise for the marketing concept is to satisfy the needs of the customer. Personal selling plays an important role in that, especially in the B2B market. Customer satisfaction has a positive impact on the company, which has been demonstrated by the research of many scholars, when customers are satisfied with the need that leads to the business being able to retain customers, bringing a positive influence from word-of-mouth marketing effects thereby bringing higher profits to the business. Enhanced customer satisfaction reduces the number of complaints a company receives thereby reducing the cost spent on complaint resolution. From the arguments above, it can be seen that measuring customer satisfaction and identifying the factors that promote satisfaction helps businesses discover methods to improve service quality thereby increasing their competitive advantage. The market where the research was conducted here is the B2B market, where individual sales activity demonstrates the most advantages in bringing satisfaction to customers.

Customer care and Customer Satisfaction

Miller and Berg have proposed three types of behaviors that can recognize employee care behavior toward customers, including obligation behavior, beneficiary behavior, and caring behavior (Miller & Berg, 1984). Goad & Jaramillo (2014) have shown that care is how customers feel when they receive employee attention. As the Theory of Fairness, individuals tend to help those who have helped those (Goad & Jaramillo, 2014). However, it is not excluded that dishonesty is for immediate business purposes. This study assumes that employee customer care stems from the Fairness theory.

The level of customer care behaviors, which make customers satisfied, is based on employee motivation. According to f and Berg there are three behaviors: mandatory care, caring about achievement goals, and caring about the desire to have a motivation to make customers feel satisfied (Miller & Berg, 1984). Dishonest interest still appears in business transactions, but this study focuses solely on care stemming from sincere affection in the relationship between customers and employees. Caring behavior driven by a desire to make customers satisfied can lead to higher levels of customer satisfaction. Based on Kaladhar's research, the level of business success now depends first and foremost on customer care, building good relationships between customers and individual salespeople will win customer satisfaction rather than just focusing on selling products (Kaladhar, 2016). Due to these arguments, the H1 hypothesis is given as follows:

H1: Customer care has a positive impact on customer satisfaction

Personal Connection and Customer Satisfaction

Individuals found to have many of the same personalities were more likely to form personal connections (Duck, 1976). Personal connection is a strong sense of connection between individuals. These connections are usually based on some common characteristics or common interests (Gremler, et al., 2001; Duck, 1976).

Personal connections are usually based on a number of common attributes (such as personality, perspective, etc.) or common interests with stakeholders. Personal connections in employee-customer interactions in personal selling influence customer perception and attitude (satisfaction) (Delcourt et al., 2013). Customer commitments can be strengthened or become weaker depending on the relationship with employees and therefore the level of satisfaction may vary accordingly. A study by Coulter & Coulter (2000) found that the same perception between customers and employees increases customer satisfaction (Coulter & Coulter, 2000). Therefore, the H2 hypothesis is proposed as follows:

H2: Personal connection between employees and customers in personal sales have a positive effect on customer satisfaction

Employee Competence and Customer Satisfaction

In a highly interactive service environment, consumers very often identify their position towards the company from their attitude towards employee competence (Athanassopoulos et al., 2001). In an environment where the products are considered the same, the only difference is the service provided by the employee. According to Ahearne and his employees' competence affects customer satisfaction, it is reflected in the following factors: Quick response to phone calls, exceeding expectations in commitments, fulfilling customer requirements, and always being available when necessary (Ahearne et al., 2007).

The competence of individual salespeople is reflected in their work style, expertise and enthusiasm (Ahearne et al., 2007). Employees can meet the needs of customers even when they are busy, or they can serve customers in a timely manner. Customers feel more satisfied when served by highly qualified staff. Lai and Rameeza show that employee competence has a positive impact on timely response to customer expectations (Lai et al., 2007; Ramezani et al., 2013). Therefore, this study proposes the H3 hypothesis as follows:

H3: The competence of individual salespeople has a positive impact on customer satisfaction

Product Knowledge and Customer Satisfaction

The knowledge of the product of the individual salesperson is the whole understanding of the products and services that their business provides. These insights include the product's features, the value of the benefits it brings to customers.

A salesperson's product knowledge is also an important factor that customers consider before making a purchasing decision (Jefriansyah et al., 2018). Several researchers have observed how product knowledge such as knowledge of costs, product attributes, and product quality affects customers' perceptions of perceived value and risk when purchase decision (Wang & Hazen, 2016). In the case of businesses dealing in products in the fields of software, chemicals, pharmaceuticals, insurance, investment packages, cars, and technical equipment, the personal selling process can convey more information. The more knowledge for buyers helps them in the purchasing decision process, the easier their needs are to be met at a higher level. Many businesses are using different promotion mixes, these include: Advertising, public relations, sales promotion, personal selling, interactive marketing. The right combination of promotional tools makes it easier for sellers to succeed in their sales process. Building personal selling activities based on the contact process between sellers and buyers allows businesses to achieve their sales goals and build a long-term relationship with their customers (Kotler & Armstrong, 2018). Efforts in personal selling increase the customer's knowledge of the product, this knowledge will assist them in making purchasing decisions, have detailed product knowledge that makes them feel more satisfied when deciding to buy the product (Kotler & Keller, 2009). From the above arguments, hypothesis H4 is presented as follows:

H4: Personal sales staff provide full product knowledge to customers to make them more satisfied

From the above hypotheses, we propose the following research model Figure 1:

Figure 1: Research Model.

Research Method

Questionnaire Design

To test the relationships we proposed above, this study uses a survey method using questionnaires to collect data. The scales used in this study are applied from previous studies with adjustments to suit the context of our research. The study used a 5-point Likert scale, from 1 to 5, respectively, from strongly disagree to completely agree. Specifically, the customer care scale includes 5 observations applied from the study of (Nam et al., 2015; Kaladhar, 2016), the personal connection scale includes 5 observations taken from studies the employee competence scale is composed of 7 observations (Ahearne et al., 2007; Ramezani, 2013), the product knowledge scale includes 5 observations (Wang & Hazen 2016; Jefriansyah et al., 2018). The satisfaction scale includes 5 observations (Harzaviona & Syah, 2020; Bambale et al., 2020).

Data Collection

The main purpose of this study is to assess the satisfaction of customers who have purchased chemical products. So the subjects for this study were all customers who had ever purchased chemicals. The pattern selection method applied in this study is the method of random sample selection. The questionnaires will be randomly distributed to guests. The questionnaire consists of 27 key questions, so according to Hair, Black, Babin, Anderson, & Tatham the minimum sample size will be 135 questionnaires. To gather the most relevant answers the questionnaire is sent to customers in all different geographical areas of the customer. The questionnaire contained 277 valid data included in the analysis, corresponding to a rate of 93.3%. The demographic information of the respondents is described as follows Table 1:

Table 1
Demographic Information
Factor Component Amount %
Gender Male 146 52,7
Female 131 47,3
  Age Under 30 years old 82 29,6
31-40 years old 98 35,4
41-50 years old 60 21,7
51-60 years old 37 13,4
  Education College 61 22
Bachelor 80 28,9
Graduate 79 28,5
Other 57 20,6

Research Results

From the research model proposed above, the study attempts to identify factors in personal sales that affect customer satisfaction and how much they influence customer satisfaction in the chemical industry. The scales used in this study are based on previous studies and adapted to the context of the chemical industry in Vietnam. All data collected we will use SPSS software to encrypt and clean the data and take further audit steps. This method is appropriate because the study focuses on relationships in the model and is consistent with a small study sample (n=277). The research model we use includes four elements: customer care, personal connection, product knowledge, and employee competence.

Verify the Reliability of the Scale

To test the reliability of the scale, the study used a rating standard of Cronbach's Alpha (Ca) coefficient with a case greater than 0.6 and a total variable correlation coefficient greater than 0.3. Observations with a Case coefficient that does not meet this standard are considered garbage variables, are not reliable enough to conduct further inspection steps, and will be excluded from the study. The results of the scale's reliability test are indicated in the Table 2 below:

Table 2
Results Of The Reliability Test Of The Scale
Variable symbols Total variable correlation Cronbach's Alpha if the variable type
Customer care scale with Cronbach's Alpha: 0.917
CC1 0.743 0.918
CC2 0.831 0.885
CC3 0.876 0.869
CC4 0.822 0.892
Personal connection scale with Cronbach's Alpha: 0.855
PC1 0.710 0.813
PC2 0.763 0.763
PC3 0.709 0.814
Employee competence scale with Cronbach's Alpha: 0.796
EC1 0.626 0.739
EC2 0.658 0.722
EC3 0.659 0.720
EC4 0.506 0.792
Product Knowledge Scale with Cronbach's Alpha: 0.846
PK1 0.764 0.784
PK2 0.709 0.800
PK3 0.669 0.811
PK4 0.549 0.841
PK5 0.603 0.828
Cronbach's Alpha Satisfaction Scale: 0.826
SA2 0.620 0.824
SA3 0.741 0.704
SA5 0.718 0.744

Through the results shown in the Table 2 above, after the type of garbage variables remained the same 5 factors with 19 observations included in the next analytical steps.

EFA Discovery Factor Analysis

The component scales of the satisfactory study in the reliability assessment will be conducted for use in efa discovery factor analysis. After testing the scales using Cronbach's Alpha coefficient, of the five elements with 19 observed variables (type 8 observed), the factor analysis was included.

KMO and Bartlett test results showed acceptance because the KMO coefficient of 0.835 >.5 and the sig.=0.000<0.05, and the Eigenvalues coefficient of 1,290 >1, which is satisfactory for EFA analysis, the analysis of factors and data collected is entirely appropriate.

The result of the factor analysis with the Principal Component extract method, using Varimax rotation, allows 4 factors to be extracted from 16 observed variables and the total varinder is 71.203%, all factors have a factor load factor of more than 0.5% Table 3.

Table 3
Efa Discovery Factor Analysis Results
Rotated Component Matrixa
  Component
X1 X2 X3 X4
CSKH3 0.907      
CSKH4 0.880      
CSKH2 0.876      
CSKH1 0.841      
KT1   0.790    
KT3   0.761    
KT5   0.743    
KT2   0.704    
KT4   0.698    
NL3     0.832  
NL4     0.769  
NL2     0.757  
NL1     0.741  
KNCN2       0.859
KNCN3       0.844
KNCN1       0.800

Simultaneously, the findings in the table above demonstrate no interference of factors, indicating that the question of one element is not confused with the question of the other. As a result of the EFA analysis, the independent factors we employed in this study remained unchanged, with no rise or decrease in the factor.

Check Correlation Coefficients

The study used correlation coefficients to examine the correlation and multilineation that occurs between variables. The test results are shown in the Table 4 below:

Table 4
Correlation Coefficient Test Results
Correlations
  X1 X2 X3 X4 Y
X1 Pearson Correlation 1 0.323** 0.146* 0.369** 0.403**
Sig. (2-tailed)   0.000 0.015 0.000 0.000
N 277 277 277 277 277
X2 Pearson Correlation 0.323** 1 0.068 0.491** 0.399**
Sig. (2-tailed) 0.000   0.257 0.000 0.000
N 277 277 277 277 277
X3 Pearson Correlation 0.146* 0.068 1 0.307** 0.373**
Sig. (2-tailed) 0.015 0.257   0.000 0.000
N 277 277 277 277 277
X4 Pearson Correlation 0.369** 0.491** 0.307** 1 0.545**
Sig. (2-tailed) 0.000 0.000 0.000   0.000
N 277 277 277 277 277
Y Pearson Correlation 0.403** 0.399** 0.373** 0.545** 1
Sig. (2-tailed) 0.000 0.000 0.000 0.000  
N 277 277 277 277 277

This result shows that the Sig. level of meaning is less than 0.05 so the variables used in the model are correlated with satisfaction.

Building a Linear Regression Model

To be able to determine the extent to which independent variables explain the independent variable we use the Adjusted R Square (R squared calibrate and R2 (R Square) values. The test results are shown in the Table 5 below:

Table 5
Linear Statistical Results
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 0.838a 0.606 0.508 0.73093 1.130

Based on the linear statistical results Table 5, there is R2 by 0.508. This result represents independent variations in the model that explain 50.8% of the variation of dependent variables, while the remaining 49.2% of the variation of dependent variables is explained by off-model variables and random errors.

The Durbin-Watson value is equal to 1,130, which is greater than 1 and less than 3. Infer that there is no similar phenomenon between variables.

Based on the Table 6 above, we see the Sig. value =0.000<0.05 this means that the data set obtained is suitable for inclusion in the analysis. The linear regression model is built in line with the whole.

Table 6
Anova Accreditation
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 99.521 4 24.880 46.569 0.000b
Residual 145.319 272 .534    
Total 244.840 276      

After the above analytical steps, it is found that the factors used are perfectly appropriate for inclusion in regression analysis. The results of the multi-variable regression analysis are shown in the Table 7 below:

Table 7
 Multi-Variable Regression Analysis Results
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) -0.350 0.264   -1.323 0.187    
X1 0.183 0.047 0.198 3.881 0.000 0.835 1.198
X2 0.163 0.055 0.161 2.946 0.003 0.727 1.375
X3 0.284 0.060 0.235 4.762 0.000 0.894 1.118
X4 0.434 0.079 0.320 5.516 0.000 0.648 1.542
a. Dependent Variable: Y

The Beta coefficient of independent variables is positive, which demonstrates that independent variables have a positive effect on dependent variables. We have the Beta coefficient of variables X1, X2, X3, X4 are: 0.198; 0.161; 0.235; 0.320 these coefficients are all greater than 0 and the Sig. coefficient of t in the verification of the hypothesis is less than 0.05 so it can be argued that the H1 hypothesis, H2, H3, H4 are all acceptable.

We obtain a regression shape that is represented in the following form:

Y=0.198X1+0.161X2+0.235X3+0.320X4

Y: Variable value depends on "Customer satisfaction"
X1: Independent variable value "Customer care"
X2: Independent variable value "Personal connection"
X3: Independent variable value "Employee competence"
X4: Independent variable value "Product knowledge"

In summary, customer satisfaction is positiveally affected by the knowledge variables, employee competence, customer care, personal connection in descending order.

Discussions on Research Results

In an economy with a chemical industry that does not have many advantages of Vietnam; chemical enterprises are facing fierce competition from FDI enterprises. With the characteristics of the chemical industry, the sales strategy is one of the important factors that create the success of the business, moreover, this is also a factor to help the domestic chemical enterprise create a competitive advantage.

The main purpose of the study is to examine what factors in personal selling affect customer satisfaction in the chemical industry, while also trying to clarify how influential the determinants have on customer satisfaction. The results of the study indicate that factors in personal sales influence the satisfaction of customers buying chemicals. Specifically, research indicates that there are four factors: customer care, personal connection between seller and buyer, knowledge of products or the employee competence of sellers are factors that directly affect customer satisfaction. Of these factors, sellers' product knowledge is the most powerful factor on customer satisfaction (β=0.320), chemicals are specific products, so the seller's provision of full information about the product makes buyers feel more secure (Bambale et al., 2020) which in turn makes them feel better. Employee competence a factor that affects customer satisfaction that we find, the capacity within the framework of the research is understood as the ability to understand customers, convince customers, spend time with consumers, make use of resources to aid the service process, and always assist customers in completing the purchase process as swiftly as possible. This finding further reinforces the authenticity of previous scholarly studies such as the study of (Ahearne, 2007; Ramezani et al., 2013). This study also indicates that companies' customer care towards customers also increases their satisfaction (β=0.198), the results of which are similar to the results of several studies South 2015 (Kaladhar, 2016). Finally, this study demonstrates that the personal connection between sellers and buyers is also a factor that affects buyer satisfaction. These findings have made an important contribution to real reasoning, in addition to supporting many previous views, they also contribute and some important findings to the theory of personal selling activities in Vietnam.

Besides the contributions to reasoning, this study also has a number of findings that contribute to practice. In order to increase satisfaction levels and retain customers, businesses should organize training courses aimed at providing their employees with knowledge about chemicals and chemicals so that salespeople can communicate to customers clearly, It is easy to understand the information about chemical products that our company provides. At the same time, chemical companies should focus on providing employees with situational knowledge, such as creating cases of defective chemical products to help employees understand why the product that their company provides is defective, allowing them to provide passengers with a suitable solution. It helps increase their satisfaction with the business. Furthermore, this aids firms in identifying ineffective management and transportation in order to provide appropriate solutions to cut expenses and improve corporate performance.

Next, the study found that seller competence is a factor that has a strong impact on customer satisfaction. From here, managers should develop appropriate plans to improve the capacity of their sales team. The competencies we mentioned in this study include the ability to recognize customer needs, the ability to support customers in a timely manner, the ability to convince customers that salespeople know what customer concerns are from which to always advise customers on the right products for their needs, the ability to effectively use the tools to support the sales process and understand the procedures for entry, transportation of chemicals and handle these procedures quickly.

Third, the study found that customer service in personal sales has a positive effect on customer satisfaction, and the study also suggests that chemical companies should invest more in customer care activities both before and after sales, Ensure that salespeople always remember the customer's name and contact customers with a gentle, polite attitude and inform them of the latest information about the programs that the company is organizing.

Finally, research indicates that personal connections are also a factor that has a positive impact on customer satisfaction. This finding provides these managers with a basis for formulating the right personal sales strategy.

Conlcusion

In addition to the contributions to this theory and practice of research, there are also some limitations. First, the study had limitations on the sample, the sample size we used was n=277 sample sizes and it was not representative. We only collect information from customers who buy chemicals. Future research may look at expanding sample sizes by gathering more customer information in a number of other areas of business.

The next limitation of the study is that the document only examines and demonstrates a number of factors that affect customer satisfaction. Further studies can expand the research by adding some new variables, looking at intermediary relationships from personal sales that affect customer satisfaction. Therefore, future studies may look at the issues we have just covered to contribute further to reasoning as well as practice.

References

Adesoga, A. (2016). Examination of the relevance of personal selling in marketing activities: A descriptive method. Journal of Accounting and Management, 6(2), 103-116.

Google Scholar

Ahearne, M., Jelinek, R., & Jones, E. (2007). Examining the effect of salesperson service behavior in a competitive context. Journal of the Academy of Marketing Science, 35(4), 603-616.

Indexed at, Google Scholar, Cross Ref

Athanassopoulos, A., Gounaris, S., & Stathakopoulos, V. (2001). Behavioural responses to customer satisfaction: an empirical study. European Journal of Marketing, 35(5/6), 687-707.

Indexed at, Google Scholar, Cross Ref

Ayimey, E.K., Awunyo-Vitor, D., & Abdulai, S. (2013) Influence of Customer Retention Strategies on performance of SIC Life Insurance Company Limited and StarLife Assurance Company Limited in Ghana: An Exploratory Assessment. International Journal of Business and Managermant, 7(3), 89-94.

Bambale, S.A., Ghani, M.B.A., & Ado, A.B. (2020). How Service Quality Affects Customer Satisfaction: A Study of Malaysian Electric Train Service (ETS). Journal of International Business and Management, 3(2), 01-07.

Indexed at, Google Scholar

Banerjee, A. (2013). The role of personal selling in home insurance in Indian market. International Journal of Business and Management Invention, 2(1), 34-39.

Google Scholar

Carver, C.S., & Scheier, M.F. (1982). Control theory: A useful conceptual framework for personality–social, clinical, and health psychology. Psychological Bulletin, 92(1), 111.

Google Scholar, Cross Ref

Cheserem, E. (2016). The Influence of Marketing Mix Strategies on Customer Loyalty in Fast Food Restaurants in Nairobi, Kenya (Doctoral dissertation, University of Nairobi).

Google Scholar

Coulter, K.S., & Coulter, R.H. (2000). The effects of service representative characteristics on trust: the moderating role of length of relationship. In American Marketing Association. Conference Proceedings. 11(1). American Marketing Association.

Google Scholar, Cross Ref

Delcourt, C., Gremler, D.D., Van Riel, A.C., & Van Birgelen, M. (2013). Effects of perceived employee emotional competence on customer satisfaction and loyalty: The mediating role of rapport. Journal of Service Management, 24(1), 5-24.

Indexed at, Google Scholar, Cross Ref

Dennis, A.R., Yuan, L., Feng, X., Webb, E., & Hsieh, C.J. (2020). Digital nudging: Numeric and semantic priming in e-commerce. Journal of Management Information Systems, 37(1), 39-65.

Indexed at, Google Scholar, Cross Ref

Duck, S. (1976). Interpersonal communication in developing acquaintance. Explorations in Interpersonal Communication, 5, 127-147.

Google Scholar

Goad, E.A., & Jaramillo, F. (2014). The good, the bad and the effective: a meta-analytic examination of selling orientation and customer orientation on sales performance. Journal of Personal Selling & Sales Management, 34(4), 285-301.

Indexed at, Google Scholar, Cross Ref

Gremler, D. D., Gwinner, K.P., & Brown, S. W. (2001). Generating positive word?of?mouth communication through customer?employee relationships. International Journal of Service Industry Management,12(1), 44-59.

Indexed at, Google Scholar, Cross Ref

Harris, E.G., Mowen, J.C., & Brown, T.J. (2005). Re-examining salesperson goal orientations: personality influencers, customer orientation, and work satisfaction. Journal of the Academy of Marketing Science, 33(1), 19-35.

Indexed at, Google Scholar, Cross Ref

Harzaviona, Y., & Syah, T.Y.R. (2020). Effect of customer satisfaction on customer loyalty and marketing organization performance in B2B market over heavy equipment company. Journal of Multidisciplinary Academic, 4(4), 242-249.

Google Scholar

Jefriansyah, F., R. Wahdiniwaty, K. Suryadi & D. S. Aprilliani, Jefriansyah, F., Wahdiniwaty, R., Suryadi, K., & Aprilliani, D. S. (2018). Improving product knowledge through personal selling activities. In International Conference on Business, Economic, Social Science and Humanities.

Google Scholar, Cross Ref

Jumaev, M., & Hanaysha, J. R. (2012). Impact of relationship marketing on customer loyalty in the banking sector. Far East Journal of Psychology and Business, 6(4), 36-55.

Google Scholar

Kaladhar, C. (2016). A study on customer satisfaction and customer care support in car servicing industry with reference to the state of Andhra Pradesh. International Journal of Advance Research in Computer Science and Management Studies, 4(2), 45-52.

Google Scholar

Kotler, P., & Armstrong, G. M. (2018). Marketing Mix: Selected Chapters From: Principles of Marketing, Philip Kotler and Gary Armstrong. Pearson.

Indexed at, Google Scholar

Kotler, P., & Keller, K.L. (2009) Marketing Management. New Jersey, USA: Pearson Education, Inc.

Kwak, H., Anderson, R.E., Leigh, T.W., & Bonifield, S.D. (2019). Impact of salesperson macro-adaptive selling strategy on job performance and satisfaction. Journal of Business Research, 94, 42-55.

Google Scholar, Cross Ref

Lai, F., Hutchinson, J., Li, D., & Bai, C. (2007). An empirical assessment and application of SERVQUAL in mainland China's mobile communications industry. International Journal of Quality & Reliability Management, 24(3), 244-262.

Google Scholar, Cross Ref

Lynch, P., O'Toole, T., & Biemans, W. (2016). Measuring involvement of a network of customers in NPD. Journal of Product Innovation Management, 33(2), 166-180.

Indexed at, Google Scholar, Cross Ref

Mbugua, D.M. (2014). Personal selling strategies and performance of pharmaceutical firms in Nairobi, Kenya.

Google Scholar

Miller, L.C., & Berg, J.H. (1984). Selectivity and urgency in interpersonal exchange. In Communication, intimacy, and close relationships, 161-205. Academic Press.

Indexed at, Google Scholar, Cross Ref

Moghareh Abed, G., & Haghighi, M (2016). The effect of selling strategies on sales performance: Case study of insurance firms in Bingley, United Kingdom. Business Strategy Series, 10(5), 266-282.

Google Scholar

Nam, P.N., Ha, N.M, & Dung, N.H (2015). Impact of relations between employees and customers to the customers’ positive word-of-mouth in real estate industry. Journal of Science, (4), 16.

Indexed at, Google Scholar

Ocon, J.A.C., & Alvarez, M.G. (2014). The implication of personal selling strategies in motivation, approaches and good grooming. Procedia-social and Behavioral Sciences, 155, 53-57.

Indexed at, Google Scholar, Cross Ref

Ramezani, M., Bashiri, M., & Tavakkoli-Moghaddam, R. (2013). A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Applied Mathematical Modelling, 37(1-2), 328-344.

Indexed at, Google Scholar, Cross Ref

?en Küpeli, T., & Özer, L. (2020). Assessing perceived risk and perceived value in the hotel industry: an integrated approach. Anatolia, 31(1), 111-130.

Indexed at, Google Scholar, Cross Ref

Singh, J., Flaherty, K., Sohi, R. S., Deeter-Schmelz, D., Habel, J., Le Meunier-FitzHugh, K., & Onyemah, V. (2019). Sales profession and professionals in the age of digitization and artificial intelligence technologies: concepts, priorities, and questions. Journal of Personal Selling & Sales Management, 39(1), 2-22.

Indexed at, Google Scholar, Cross Ref

Wang, Y., & Hazen, B.T. (2016). Consumer product knowledge and intention to purchase remanufactured products. International Journal of Production Economics, 181, 460-469.

Indexed at, Google Scholar, Cross Ref

Yan, K., & Berliner, D.C. (2013). Chinese international students' personal and sociocultural stressors in the United States. Journal of College Student Development, 54(1), 62-84.

Indexed at, Google Scholar, Cross Ref

Received: 17-Dec-2021, Manuscript No. AAFSJ-21-10520; Editor assigned: 20-Dec-2021, PreQC No. AAFSJ-21-10520(PQ); Reviewed: 03-Jan-2022, QC No. AAFSJ-21-10520; Revised: 06-Jun-2022, Manuscript No. AAFSJ-21-10520(R); Published: 13-Jun-2022

Get the App