ANALISIS PSIKOLOGIS KONDISI SISWA TAMAN KANAK-KANAK SEBELUM DAN SESUDAH MENEMPATI GEDUNG TK PROGRAM PENGEMBANGAN KECAMATAN (PPK) REHABILITASI PASCA GEMPA 2006

Corresponding Author: Ardiwiriyanata

INTRODUCTION

In the current era, the pandemic period requires people to spend more time at home, so the trend for health and beauty care is increasing; this is shown by the increase in the cosmetic industry in Indonesia, according to the Central Statistics Agency in the first quarter of 2020, which increased by 5.59%. It is projected to grow by 7% in 2021 (Rizati, 2021). The following is data on the best-selling care products in Indonesia.

Figure 1. 10 Best-Selling Brands of Body Care Products

In Indonesia, the cosmetics industry has various sub-industries, including the hair care sub-industry. Research conducted by Farah Ramadhani (2021) shows the proportion of market share as follows:

Gambar 2. Market Share Produk Perawatan Rambut di Indonesia

Based on the data above, one of the players in the hair care sub-industry is PT. Rantaeus Cipta Pesona, with the Venon brand, is currently a follower in the Indonesian market share. As a company that wants to continue to grow, it wants to continue increasing its market share and becoming a market leader. To reach the market leader point, the company can continue increasing product sales. One of the spearheads of sales is sales at the company's forefront.

The relationship between SOCO by Sales and boundary-spanners has been proven ( (Frankwick et al ., 2001) and (Schultz & Good, 2000), with boundary-spanners as activities, & behaviors carried out by Sales to all customers within the company and outside (Abel et al., 2021). Few people deny that the Impact of companies pursuing long-term relationships has benefits (Yi & Amenuvor, 2022). The Sales Oriented ï¿½ Customer oriented (SOCO) approach is becoming a standard mechanism for analyzing the trend of boundary-spanners for relational marketing (Saxe & Weitz, 1982). Customer orientation strategies are more likely to form long-term relationships with Sales ( (Elistia & Rizan, 2009) ; (Amenuvor, Basilisco, et al ., 2022); and (Schultz & Good, 2000). Customer orientation focuses on providing assistance and solutions to customers in making informed purchasing decisions and prioritizing measures in customers' best interests rather than direct sales and commissions (Yi & Amenuvor, 2022). On the other hand, sales-oriented strategies are not so concerned with customer interests but transactions. Quick and simple to complete. Most salespeople believe that sales orientation is not fixed and contradicts customer orientation (Wachner et al ., 2009).

Regardless of the importance of boundary-spanner sales, a significant gap still needs further investigation. For example, the activity of reaching strategic sales limits requires specific capabilities, in previous research was not too focused on measuring these individual capabilities and how these capabilities can generate sales behavior. As well as the nature of sales work requires sales to achieve its goals. Nonetheless, several studies have been conducted regarding the effect of SOCO sales being influenced by their specific sales skills. Therefore, this study focuses on how SOCO behavior is related to sales and sales performance is influenced by the intensity of competition. In addition, previous studies (Yi, Cha, et al ., 2021) and (Yi, Yeo, et al ., 2021) state that several studies have been conducted on subjects at sales by placing less focus on how SOCO behaves customer-oriented and sales -oriented sales have an influence on sales performance. Therefore, to fill this gap, this research was conducted to model the effect of individual sales ability on sales-oriented and customer-oriented sales behavior. However, previous research only focused on B2C sales, so this research will focus on B2B sales and investigate how sales-oriented and customer-oriented sales behavior affect sales performance. The next GAP in this study is the method used for primary data analysis using the structural equation modeling (SEM PLS) method.

This study aims to explore how the sales ability of individual sales influences sales-oriented and customer-oriented sales behavior. This study also aims to add to the development of knowledge by looking at the role of sales-oriented and customer-oriented sales behavior in sales performance and the moderating effect of competitive intensity with the same relationship. This research has the benefit of improving understanding of the factors that affect sales performance. This research can also help in understanding the factors that affect sales performance, especially in terms of the role of sales oriented and customer-oriented sales behavior, as well as how moderation in competition intensity can affect the relationship. This research can show the importance of orientation on customers in sales performance. Sales oriented and customer-oriented sales behavior can affect sales performance differently, and customer orientation can play an important role in improving sales performance.

METHOD

This research uses quantitative research methods. This research was conducted by collecting data using an online questionnaire survey method via Google Forms as a data collection technique; the data collected was in the form of scores from the respondents. Furthermore, the data that was successfully collected will be measured using the Likert scale method, which has five alternative answers, namely on a score of five assessments strongly agree (SS), a score of four assessments agree (S), a score of three assessments between agreeing and disagreeing (N), a score of two assessment disagree (TS) and score one assessment strongly disagree (STS) (Munshi, 2014). Measurement of the research variables adopted from measurements consisting of 5 statements, Salesperson's Sales Capability variable (12 questions) adapted from Spencer and Spencer (1993) Customer-Oriented Selling Behavior variables (7 questions), and Sales-Oriented Selling Behavior (6 questions) from Saxe and Weitz (1982), Sales Performance variable (6 questions) from Behrman & Perreault in Wachner et al., (2009), and the Competitive Intensity variable (5 questions) from Jaworski, BJ, Kohli, (1993). Precisely, competitive intensity is measured by the following scale items adapted from Jaworski, BJ, Kohli (1993): CI1ï¿½Competition in the market is very tight; CI2ï¿½There are many ï¿½promotion warsï¿½ in the market; CI3ï¿½Price competition is a hallmark of the market; CI4ï¿½One often hears about new competitive moves in the market. The scale development and purification methodologies and processes proposed by DeVellis (2003), specifically for confirmatory factor analysis, were used to refine all scale items. There are 36 statements; these statements can be seen in Appendix 2 and Appendix 3.

In the validity test, using the dimension reduction factor analysis in SPSS, namely by looking at the Kaiser-Msyer-Olkin measure of sampling (KMO) and measures of sampling adequacy (MSA) values with an acceptable value of ≥0.500 (Hair et al., 2021). The Salesperson's Individual Sales Capability variable is declared valid (0.699> 0.5), Sales-Oriented Selling Behavior is declared valid (0.770> 0.5), Customer-Oriented Selling Behavior is declared valid (0.699> 0.5), Competitive Intensity is declared valid (0.756> 0.5), Sales Performance is declared valid (0.880> 0.5). Furthermore, on the reliability test results, all variables were declared reliable with a Cronbach Alpha value of > 0.5, according to (Hair et al., 2021).

The population in this study is the B2B sales of the hair care industry. To determine the Validity and reliability of each statement to be used in the questionnaire, this study tested the factor analysis method and to determine the level of significance and interrelationships between each variable using the structural equation model (SEM) analysis method. Based on the SEM analysis method, determining the number of research samples is five times the number of statements (Hair et al., 2021). This study uses a minimum sample of (36x5) 180 respondents.

RESULTS AND DISCUSSION

Validity and Reliability Test (pretest)

The KMO test or Kaiser-meyer-olkin (KMO) and Bartlett's test in this study were used to test the Validity of the research questionnaire. The KMO value that must be met for each variable is > 0.50, with Bartlett's test value of < 0.05. Later, these variables can be analyzed further (Napitupulu et al., 2017). The MSA value that must be fulfilled for each variable indicator is > 0.50. If the question indicator has an MSA value of < 0.5, then the indicator must be discarded and not included in further research. Based on the data processing results, the results of 5 variables in this study met the requirements of the KMO test and Bartlett's test. In addition, the MSA value for each indicator was > 0.50. It can be concluded that all research variables and indicators can be used for further analysis. The reliability test was carried out referring to the Cronbach alpha value. The rule for generally accepted α values is 0.6-0.7, meaning reliability is acceptable (Ursachi et al., 2015). Based on the calculation results, it is known that all indicators of the questionnaire questions used meet the reliability test requirements with Cronbach alpha > 0.70, meaning that the research indicators are said to be reliable.

Convergent Validity Test

The magnitude of convergent Validity can be seen by looking at the value of the loading factor in the outer loading table and can also be seen by the magnitude of the AVE value or average variance extracted. The loading factor value is > 0.70 and > 0.5 for the AVE value, which is a constant that must be met to measure convergent Validity (Hair et al., 2021). In this study, the results obtained for 36 indicators had a value of > 0.70. Indicators that have an outer loading value of not less than 0.4 and less than 0.7, these indicators can still be considered for maintenance (Hair et al., 2021). Therefore, the measurement result, namely convergent Validity for the 36 indicators, has been fulfilled. Convergent Validity All variables were declared valid with the criterion of AVE > 0.7, while the Competitive Intensity variable was declared unreliable with Cronbach's Alpha measurement standard <0.7.

Discriminant Validity Test

Using empirical standards, discriminant Validity illustrates that one latent variable is different from the other. The cross-loading value of each indicator of the latent variable can explain the discriminant validity test. Cross-loading value shows the correlation between an indicator to its construction and other constructs. The correlation value of the indicator to the latent variable needs to show more significant results than the correlation value to the other latent variables. Based on the results of data processing using Smart-PLS, it is known that all variables meet the requirements of good discriminant Validity.

Internal Consistency Reliability Test

The Composite reliability value can measure the internal consistency reliability test in SEM-PLS. The Composite reliability value can be reliable if it has a value > 0.7 (Hair et al., 2021). Based on the calculations, the results show that all latent variables (constructs) have a Composite reliability value of > 0.70. Except for the Competitive Intensity variable (0.696).

Coefficient of Determination (Adjusted R2)

The value of the coefficient of determination explains to what extent exogenous variables can explain endogenous variables. Based on calculations, it is known that the variables from the output value are Customer-Oriented Selling Behavior at 62.6%, Sales-Oriented Selling Behavior at 94.9%, and Sales Performance at 88%.

Details of construct measurements are shown in the table below:

Tabel 1. Coefficient of Determination (Adjust R2)

	Cronbachï¿½s Alpha	Composite Reliability (Rho_A)	Composite Reliability (Rho_C)	Average Variance Extracted (Ave)
Competitive Intensity	0.686	0.696	0.864	0.760
Customer Oriented	0.879	0.891	0.912	0.676
Sales Individual	0.963	0.967	0.967	0.731
Sales Oriented	0.853	0.855	0.895	0.630
Sales Performance	0.918	0.927	0.937	0.712

Based on the distribution of questionnaires conducted online via the Google form, 180 respondents were collected according to predetermined criteria. From the data obtained, the number of respondents was categorized by age, namely 20 ≤30 by 41%, 30≤40 by 37%, and 40 ≤ 50 by 22%. Furthermore, based on respondents' education level, 31% at the high school level, 69% at the BACHELOR level, and 0% at the SMP level. Furthermore, based on the workplace, 40% of the respondents worked at the principal, and 60% worked at the Distributor. Furthermore, based on the respondent's tenure in the company, namely 1≤3 years as much as 14%, 3≤5 years as much as 25%, 5≤7 years as much as 22%, and ≥ seven years as much as 39%. Furthermore, based on respondents' positions, 38% work as Sales Executive, 18% work in Sales Promotion, and 44% work in Direct Sales.

Path Coefficient Significance (Hypothesis Test)

Testing the hypothesis in this study can be seen through the significance of the path coefficient. Path coefficient significance values can be obtained using bootstrapping techniques with Smart-PLS software. According to (Hair et al., 2021), if the p-value <0.05, it can be said that there is a significant influence, while the direction of the relationship can be determined by looking at the original sample value.

Tabel 2. Path Coefficient Significance

Relations Between Variables	Hypothesis	Original Value	P Value
ISC -> Customer-Oriented Selling Behavior	H1	-0.792	0.00
ISC -> Sales-Oriented Selling Behavior	H2	0.974	0.00
Customer-Oriented Selling Behavior -> Sales Performance	H3	-0.147	0.00
Sales-Oriented Selling Behavior -> Sales Performance	H4	0.653	0.00
Competitive intensity -> Customer-Oriented Selling Behavior -> Sales Performance	H5	-0.081	0.02
Competitive intensity -> Sales-Oriented Selling Behavior -> Sales Performance	H6	0.040	0.105

Based on the table above, the results obtained for all hypotheses are acceptable (H1, H2, H3, H4, H5, H6). a negative direction (-0.792) between Individual Sales Capability (X1) and Customer-Oriented Selling Behavior (X3) thus H1 cannot be accepted. Testing H2, the effect of Individual Sales Capability (X1) on Sales-Oriented Selling Behavior (X2) obtained a P value of 0.00 <0.05, so it can be said that Individual Sales Capability (X1) has a significant and positive influence on Sales-Oriented Selling Behavior (X2) with Thus H2 is acceptable. Testing H3, the influence of Customer-Oriented Selling Behavior (X3) on Sales Performance (X5) obtained the result P value 0.00 > 0.05, so it can be said that there is a significant influence but has a negative direction (-0.147) between Customer-Oriented Selling Behavior (X3) on Sales Performance (X5) thus H3 is unacceptable. Testing H4, the effect of Sales-Oriented Selling Behavior (X2) on Sales Performance (X5) obtained a P value of 0.00 <0.05, so it can be said that there is a significant and positive influence between Sales-Oriented Selling Behavior (X2) on Sales Performance (X5) thus H4 acceptable. The H5 test regarding the effect of Competitive Intensity (X4) which moderates the relationship between Customer-Oriented Selling Behavior (X3) on Sales Performance (X5), obtained the results of P value 0.02 <0.05, so it can be said that there is a significant influence but negatively. Based on the results of the SLOPE test, an analysis of the Competitive Intensity moderating variable obtained the pattern as shown in the diagram below.

Figure 3. Competitive Intensity X Customer Oriented

Testing H6 regarding the influence of Competitive Intensity (X4) which moderates the relationship between Sales-Oriented Selling Behavior (X2) and Sales Performance (X5) results obtained a P value 0.105 <0.05, so it can be said that there is no moderating effect.

Based on the analysis results, there is a relationship between Individual Sales Capability and Customer-Oriented Selling Behavior. This relationship is influenced by a salesman's analytic thinking patterns, the drive to build a sales network/human network, and organizational recognition. This is because Individual Sales Capability will impact Customer-Oriented Selling Behavior. However, the higher the ability of individual Venon sales clerks will reduce the sales orientation focusing on customer interests. Because sales are starting to think about the result, namely the sales target given to evaluate its performance compared to the process of fostering outlets such as the principle of Customer-Oriented Selling Behavior where the stages in building good relationships, meeting customer needs, or fulfilling customer requests are to increase customer satisfaction which in the end the customer will fulfill sales needs. However, this process is considered by sales associates to be time-consuming and complex, which allows salespeople to think analytically in the interest of increasing sales volume by distributing goods or sales volume as wide as possible from Vernon rather than relying on existing outlets so that they can meet the targets set by the company. This salesman's mindset may encourage sales associates to build as many sellers (store) network relationships so that salespeople are oriented to looking for prospects for new stores or opening new customers and opening new areas on a large scale or frequency rather than managing existing stores and satisfy it (Customer-Oriented Selling Behavior). This is also due to the high competition culture within the company's internal organization, which spurs the level of competition among salespeople so that all sales compete to get recognition from the company, so they ignore Customer-Oriented Selling Behavior. The Impact is that too many outlets have to be fostered regularly, resulting in reduced salesman capacity in building or maintaining relationships with outlets.

Based on the analysis results, there is a relationship between Individual Sales Capability and Sales-Oriented Selling Behavior. The salesman's analytic thinking factor influences this relationship. This means that the greater the Individual Sales Capability, the greater the orientation of the Sales-Oriented Selling Behavior. This is because Sales will think of achieving the targets given by the company by prioritizing transactions with outlets, especially outlets with large transaction volumes. The greater the sales target will generate a sales mindset to increase sales volume by relying on the capabilities possessed. By capitalizing on broad insights, salespeople will market and distribute products to prospective outlets that are right on target so that transactions are more likely to occur. Relying on close personal relationships with outlets, making it easier for sales to ask for help from outlets in transactions. Opening new outlets will encourage salesman performance with greater expectations in terms of sales volume compared to building existing and limited outlets. This Sales-Oriented Selling Behavior orientation will form itself over time with more fantastic encouragement, demands, and responsibility from the company.

Based on the analysis results, there is a relationship between Customer-Oriented Selling Behavior and Sales Performance. Factors and Accurate information about the product influence this relationship. This means that the greater orientation of sales toward Customer-Oriented Selling Behavior results in decreased Sales Performance. This happens because sales perceptions play a significant role in transaction decisions. If sales feel less confident, it will impact sales performance. Sales become worried about arguing with the outlet because it can spoil the atmosphere of the conversation with the outlet; this becomes doubtful for the salesperson to push his argument with consideration of the outlet's requirements for his needs so that the presentation delivered will be less attractive to most outlets. Because the real needs of outlets are profits and not the product's benefits, as long as the product can generate large profits and has a good sales cycle, outlets will be willing to invest their capital. Sales' lack of confidence hinders outlets from making transactions because they assume Venon's product is not the solution to store needs.

Based on the analysis results, there is a relationship between Sales-Oriented Selling Behavior and Sales Performance. This relationship is influenced by the atmosphere of communication with outlets. The better sales are in building personal relationships and communication with a pleasant atmosphere will encourage sales. This means that with encouragement from sales to help market Venon products, of course, outlets will feel reluctant, increasing the possibility for outlets to transact or collaborate. Sales also try to increase sales by prioritizing the products he will sell, such as products that can generate significant sales or offer new products launched by the company. Sales will try to achieve the targets given by the company, so the target outlets are usually capable of generating large sales, such as Pareto outlets.

Based on the analysis results, Competitive intensity moderates the relationship between Sales-Oriented Selling Behavior and Sales Performance. The promotion war factor influences this moderation. The higher the level of competition or competition in the market it will encourage increased sales. This means that sales-oriented sales will try harder to maximize sales of their products; generally, for sales that apply SO (Sales-Oriented), every offer made by competitors to outlets is undoubtedly a challenge for them and will be countered with better offers. The higher the competition, the greater the sales motivation in implementing the strategy. Sales-oriented sales generally will not allow themselves to experience defeat when facing competition at outlets.

Based on the analysis results, Competitive intensity moderates the relationship between Customer-Oriented Selling Behavior and Sales Performance. This moderation is influenced by the promotion war factor that occurs in the market. The higher the level of competition in the market, the lower the sales will be. This means that promotion wars in the market often make it difficult for salespeople to fulfill the aspects needed by outlets. Promotion wars often occur so that competitors offer better offers. Generally, a customer-oriented salesperson will feel unsure of the offer he has/is motivated. This obstacle resulted in a decrease in the organization's sales performance towards customer-oriented sales.

CONCLUSION

The results of testing the entire hypothesis show that Individual Sales Capability has a positive and significant influence on Sales-Oriented Selling Behavior, besides that Sales-Oriented Selling Behavior can significantly influence Sales Performance. As for the others, Individual Sales Capability and Customer-Oriented Selling Behavior have a significant influence. However, they have a negative direction. The result of the following test is that Customer-Oriented Selling Behavior has a significant influence but negatively impacts Sales Performance. Furthermore, Competitive Intensity does not moderate the relationship between Sales-Oriented Selling Behavior and Sales Performance. Furthermore, Competitive intensity moderates the relationship between Customer-Oriented Selling Behavior and Sales Performance.

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