International Journal of Management Science and Business Administration
Volume 8, Issue 3, March 2022, Pages 24-30
The Impact of Working Capital and Production Costs on Consumer Behavior and Sales Turnover at LQ45 Manufacturing Companies in 2015-2020
DOI: 10.18775/ijmsba.1849-5664-5419.2014.83.1003
URL: https://doi.org/10.18775/ijmsba.1849-5664-5419.2014.83.1003
1 Sasriani Wida Nurhetty, 2 Candra Sinuraya
1,2 Accounting Departement, Universitas Kristen Maranatha, Indonesia
Abstract: This study aims to analyze the impact of working capital and production costs on consumer behavior, as well as the impact of working capital and production costs toward sales turnover in the Covid-19 era in LQ45 manufacturing companies on the IDX in 2015-2020. This research is quantitative research with hypothesis testing. The population in this study are all companies members of LQ45 in 2015-2020. The research uses a non-probability sampling technique with the purposive sampling method. Based on the results of hypothesis testing with simple linear regression, for Hypothesis 1, it was found that there is no effect of working capital on consumer behavior. The result found hypothesis 2, there is an effect of working capital on sales turnover. Result for hypothesis 3 found that, there is no effect of production costs on consumer behavior and for the hypothesis 4, there is an effect of production costs on sales turnover. It result of the study suggested that the impact of working capital on sales turnover can be an indicator that the company is implementing more effective production and marketing development. Meanwhile, the impact of production costs on sales turnover means that an increase in production costs indicates the company is investing in products with more excellent quality.
Keywords: Working capital, Production costs, Consumer behavior, Sales turnover
1. Introduction
Business activities are strongly influenced by macro and microeconomic factors in a country. Along with the Covid-19 pandemic, which has become a global epidemic, including Indonesia is no exception experiencing the impact of this pandemic. Corona Virus Disease 2019 (Covid-19) has a significant impact on various aspects of people’s lives everywhere. This article discuss the impact of Covid-19 on the industrial sector and the competence of the workforce in Indonesia.
Based on data disclosed Kementerian Perindustrian (Ministry of Industry) (2021), based on economic data on a year scale, the non-oil and gas processing industry in the first quarter experienced a decline in the growth rate of up to 2.01%, due to Covid-19 reaching minus in the second quarter that is equal to 5.74%. The impact of the decline in productivity during this pandemic period is that the utilization of the non-oil and gas sector has also decreased by 59%. This value is known to occur from April 2020 to November 2020, even until March to August, a decline of up to 50% occurred in industrial utilities in various sectors and sub-sectors. This condition is estimated that the non-oil and gas processing industry will contract with an improvement in growth of minus 2.22% by the end of 2020 (kemendag.go.id, 2021).
In Indonesia, the manufacturing sector on the IDX, which is protected as Manufacturing Stocks/Manufacturer Index, consists of 3 sectors, namely Basic Industry, Miscellaneous Industry, and Consumer Goods. In this study, researchers are interested in researching manufacturing companies members of LQ45. The LQ45 index was first launched in February 1997, but to obtain more detailed data, it was used on July 13th, 1994, with an index value of 100.
The LQ45 index can be interpreted as 45 issuers that have passed the assessment stage of companies with excellent liquidity and several other selection criteria (CIMBniaga.com, 2021). These criterias may include consideration of market capitalization. Forty-five issuers are adjusted every six months (early February and August). Therefore, there will be various changes to the criteria so that shares can be included in the LQ45 index, and among them are always on the IDX list in the last three months, good financial conditions, future growth, and also large transaction values. They are included in 60 shares according to the stock exchange for at least the last 12 months. Enter the stock with the highest capital at least two months before, and of the 60 stores, the 30 highest supplies will automatically enter the LQ45 index.
Until now, LQ45 has become a benchmark for stock conditions, because it functions as a composite index in addition to the JCI. The LQ45 stocks are known as superior stocks and can provide large profits. To determine which shares are included in the LQ45 index, there are two stages of requirements, namely according to the criteria, namely the claims are included in the highest 95% of the average total annual share transaction value on the regular stock exchange, and are ranked in the top 95% of the average. The average issuer with an average total share transaction value in capital and listed on the IDX within 30 stock market days. (Polakitan, 2015). Thus, if investors invest in LQ45 shares, they are expected to generate profits. However, during the Covid-19 pandemic, researchers are interested in seeing the influence of the company’s internal factors in the form of business capital and production costs on consumer behavior and sales turnover in manufacturing companies in LQ45.
The primary variable studied is Working Capital. There is a significant role of capital, because the company needs supporting capital to carry out its business activities continuously and get business profits. Business activities in a company will stop if the company does not have sufficient capital. According to Von Bohm Bawerk (in Daniel, 2017), the meaning of capital or capital is all objects or goods that are produced and found in the community, or referred to as community assets. The wealth is partly used to meet consumptive needs and is used to create new goods that have sale value and have value to society.
These two variables, namely Working Capital and Production Costs, can affect the variables of consumer behavior and sales turnover of the company. Consumer behavior describes the tendency of investors to purchase shares, which can be seen from the volume of stock transactions. The higher direction of buying, it illustrates the existence of positive direction of consumer behavior. Is the other hand, the presence of a low volume of stock transactions represents the intense interest of investors to purchase shares.
Meanwhile, Chaniago (2016) defines sales turnover as all revenue obtained from selling the company’s output, both services, and products, within a predetermined time. Meanwhile, according to Swastha (2013), sales turnover is defined as the accumulation of income from an activity selling goods or services, which is calculated in a certain period as a whole and is continuous in the accounting process. Thus, sales turnover is the entire result of selling products or services within a predetermined time, which is calculated according to the amount of revenue received, based on the volume of product sales. Companies or entrepreneurs are required to increase sales turnover continuously. Many factors can affect business conditions, namely the external and internal environment of the business itself, internal factors such as workers, machines, equipment, computers, capital, investment, mental materials, administration, communication technology, and others. In contrast, external factors include laws and regulations, natural conditions, economic and cultural conditions of a country, level of competition, suppliers, consumers, education, and others (Rachmawati, 2009).
2. Literature Review
2.1 Working Capital
Business capital is the funds used to run or establish a business or company. This capital can be in the form of energy and finance. Companies to meet business capital needs, such as pre-investment, taking care of permits and licenses, managing the cost of purchasing assets, and working operational capital, generally use finance capital. At the same time, the capital of energy or expertise is a person’s ability to carry out his business. In general, capital is a resource used to finance business activities while Riyanto, in Kasmir (2018), is running it. Working capital is used quickly and is often used many times in one production stage. (Kasmir, 2018).
2.2 Production Cost
In carrying out management functions, companies need sufficient information to plan, constrain, and make decisions. Therefore, management must have accurate and complete information regarding the company. One vital information is about cost information, or referred to as costs and expenses. This information is crucial for a company because it is needed in the production process. Charge should be classified according to the meaning for which the cost information is submitted. Therefore, to classify expenditure is based on the meaning of prices, and of course, the objectives are different (Alma, 2012).
2.3 Consumer Behavior
According to Kotler and Keller (2012), consumer behavior is the study of how a person, group, or organization makes their choices, then purchases products, uses, and puts goods, products, services, ideas, or experiences to meet their needs and satisfy their desires.
2.4 Sales Turnover
Tjiptono (2014) states that the results of selling products or services by companies benefit from these sales per unit. (Saputra, Suharyono, and Hidayat, 2016). According to Chaniago (2015), turnover is the amount of sales minus the cost of capital, production, and other expenses with the selling price. Sales turnover is the accumulated amount of sales in one accounting period. This value is seen from the number of sales in one year.
3. Methodology
This type of research is quantitative analysis (Ghozali, 2016). This study was conducted to examine the Effect of Working Capital and Production Costs on Consumer Behaviour and Sales Turnover in the Covid-19 Era at LQ45 Manufacturing Company in 2015-2020. This research is inferential/inductive research, to find the influence between variables, namely Working Capital and Production Costs on Consumer Behavior and Sales Turnover.
The population in this study are all companies members of LQ45 in 2015-2020. In this research, the writer uses a non-probability sampling technique with the purposive sampling method. The criteria for the companies studied are as follows: (1) Manufacturing companies located at LQ45 in 2015-2020, so that the impact of Covid-19 on the components studied can be seen; (2) The company has a complete financial report for the 2015-2020 period which has been audited by a Public Accounting Firm; (3) The company did not experience the delisting process from LQ45 in the research period.
4. Result and discussion
4.1 Normality Test
Table 1: Normality Test 1 and 2
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For the first Normality Test with Consumer Behavior as the dependent variable, the researcher found a significance value of 0.135. Thus, it is found that if the value of sig >. 0.05, then the data value is standard. Therefore, the Consumer Behavior data in this study has a distribution that corresponds to the standard curve. Meanwhile, for the first Normality Test with Sales Turnover as the dependent variable, the researcher found a significance value of 0.135. Thus, it is found that if the value of sig >. 0.05, then the data value is standard. Therefore, the sales turnover data in this study has a distribution that corresponds to the standard curve.
4.2 Heteroscedasticity Test
For the heteroscedasticity test with consumer behavior as the dependent variable, the researcher found that the distribution of the data obtained was reasonably even, and did not show any particular patterns. In addition, the points spread above and below zero on the y-axis, so there is no heteroscedasticity. This relatively even data distribution illustrates that the residual value has no effect on the data, which means that this study is free from heteroscedasticity symptoms. For the heteroscedasticity test with Sales Turnover as the dependent variable, the researcher found that the distribution of the data obtained was reasonably even, and did not show any particular patterns. In addition, the points spread above and below zero on the y-axis, so there is no heteroscedasticity. This relatively even data distribution illustrates that the residual value has no effect on the data, which means that this study is free from heteroscedasticity symptoms.
Figure 1: Heteroscedasticity Test 1 and 2
Table 2: Multicollinearity Test 1 and 2
| Coefficientsa | ||||||||||||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | Collinearity Statistics | |||||||||||
| B | Std. Error | Beta | Tolerance | VIF | ||||||||||||
| 1 | (Constant) | 399975407.855 | 88462753.644 | 4.521 | .000 | |||||||||||
| Working Capital (X1) | -3.646 | 4.596 | -.215 | -.793 | .430 | .167 | 6.000 | |||||||||
| Cost Production (X2) | 2.175 | 3.724 | .158 | .584 | .561 | .167 | 6.000 | |||||||||
| a. Dependent Variable: Stock Volume (Y1) | ||||||||||||||||
| Coefficientsa | ||||||||||||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | Collinearity Statistics | |||||||||||
| B | Std. Error | Beta | Tolerance | VIF | ||||||||||||
| 1 | (Constant) | 4013800.705 | 786440.863 | 5.104 | .000 | |||||||||||
| Working Capital (X1) | .022 | .041 | .014 | .540 | .591 | .167 | 6.000 | |||||||||
| Cost Production (X2) | 1.220 | .033 | .982 | 36.864 | .000 | .167 | 6.000 | |||||||||
| a. Dependent Variable: Sales Turnover (Y2) | ||||||||||||||||
For the Multicollinearity Test with the dependent variable Consumer Behavior, the VIF value is 6.000 for Working Capital and 6.000 Production Costs. Thus, this value is smaller than the VIF value, which is the benchmark of 10, which means there are no symptoms of multicollinearity. This means that the internal influence in the independent variable does not interfere with the research. For the multicollinearity Test with the dependent variable Sales Turnover, a VIF value of 6.000 is obtained for Working Capital and 6.000 Production Costs. Thus, this value is smaller than the VIF value, which is the benchmark of 10, which means that there are no symptoms of multicollinearity. This means that the internal influence in the independent variable does not interfere with the research.
Table 3: Autocorrelation Test 1 and 2
| Model Summaryb | |||||
| Model | R | R Square | Adjusted R Square | Standard Error of the Estimate | Durbin-Watson |
| 1 | .096a | .009 | -.015 | 582183039.16881 | .317 |
| a. Predictors: (Constant), Production Cost (X2), Working Capital (X1) | |||||
| b. Dependent Variable: Stock Volume (Y1) | |||||
| Model Summaryb | |||||
| Model | R | R Square | Adjusted R Square | Standard Error of the Estimate | Durbin-Watson |
| 1 | .995a | .990 | .990 | 5175653.17374 | .464 |
| a. Predictors: (Constant), Production Cost (X2), Working Capital (X1) | |||||
| b. Dependent Variable: Sales Turnover (Y2) | |||||
Based on the table above, for the calculation of Autocorrelation with Dependent Variable Consumer Behavior, the Durbin Watson value is 0.317, which is smaller than 2, which means there is no autocorrelation symptom. Thus, the tendency of these data does not indicate that there is no positive or negative autocorrelation can interfere with the results of the study.
Based on the table above, for the calculation of Autocorrelation with Dependent Sales Turnover, Durbin Watson’s value is 0.317, which is smaller than 2, which means there is no autocorrelation symptom. Thus, the tendency of these data does not indicate that there is no positive or negative autocorrelation can interfere with the results of the study.
4.3 Hypothesis Testing
The Effect of Working Capital on Consumer Behavior
The tested hypotheses are as follows:
- H1: There is an Influence of Working Capital on Consumer Behavior.
Table 4: Hypothesis Testing The Effect of Working Capital on Consumer Behavior
| Coefficientsa | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | 413639854.682 | 84968495.039 | 4.868 | .000 | |
| Working Capital (X1) | -1.196 | 1.869 | -.071 | -.640 | .524 | |
| a. Dependent Variable: Stock Volume (Y1) | ||||||
Based on the table above, the significance value is 0.524, and the t value is -0.640. Thus, reject H1, which means that there is no Effect of Working Capital on Consumer Behavior.
The Effect of Working Capital on Sales Turnover
The tested hypotheses are as follows:
- H2: There is an Influence of Working Capital on Sales Turnover.
Table 5: Hypothesis Testing The Effect of Working Capital on Sales Turnover
| Coefficientsa | |||||||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||||||
| B | Std. Error | Beta | |||||||||
| 1 | (Constant) | 11682263.661 | 3178204.326 | 3.676 | .000 | ||||||
| Working Capital (X1) | 1.397 | .070 | .911 | 19.986 | .000 | ||||||
| a. Dependent Variable: Sales Turnover (Y2) | |||||||||||
| Model Summaryb | |||||||||||
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | |||||||
| 1 | .911a | .830 | .828 | 21688590.06508 | |||||||
| a. Predictors: (Constant), Working Captial (X1) | |||||||||||
| b. Dependent Variable: Sales Turnover (Y2) | |||||||||||
Based on the table above, the significance value is 0.000, and the t-count value is 19.988. Thus, the hypothesis H2, was accepted which means that there is an effect of working capital on sales turnover. The Effect of Working Capital on Sales Turnover can be seen from KD = 0.830. Thus, the result is 83.0%.
Table 6: Hypothesis Testing The Effect of Production Costs on Consumer Behavior
| Coefficientsa | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Standard Error | Beta | ||||
| 1 | (Constant) | 398477252.921 | 88242496.556 | 4.516 | .000 | |
| Production Cost (X2) | -.522 | 1.517 | -.038 | -.344 | .731 | |
| a. Dependent Variable: Stock Volume (Y1) | ||||||
The Effect of Production Costs on Consumer Behavior
The tested hypotheses are as follows:
- H3: There is an Influence of Production Costs on Consumer Behavior.
Based on the table above, the significance value is 0.731, and the t value is -0.34. Therefore the H3 wa rejected, which means there is no effect of production costs on consumer behavior.
The Effect of Production Costs on Sales Turnover
- H4: There is an effect of Production Cost on Sales Turnover.
Table 7: The Effect of Production Costs on Sales Turnover
| Coefficientsa | |||||||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||||||
| B | Standard Error | Beta | |||||||||
| 1 | (Constant) | 4022859.933 | 782856.013 | 5.139 | .000 | ||||||
| Production Cost (X2) | 1.237 | .013 | .995 | 91.904 | .000 | ||||||
| a. Dependent Variable: Sales Turnover (Y2) | |||||||||||
| Model Summaryb | |||||||||||
| Model | R | R Square | Adjusted R Square | Standard Error of the Estimate | |||||||
| 1 | .995a | .990 | .990 | 5153235.19501 | |||||||
| a. Predictors: (Constant), Production Cost (X2) | |||||||||||
| b. Dependent Variable: Sales Turnover (Y2) | |||||||||||
Based on the table above, the significance value is 0.000, and the t-count value is 91.904. Thus, accept Ha2, which means that there is an effect of working capital on sales turnover.
The Effect of Working Capital on Sales Turnover can be seen from KD = 0.990. Thus, the result is 99%.
5. Conclusions and Recommendations
5.1 Conclusion
Based on the results of existing research, conclusions can be made as follows:
- For Hypothesis 1, there is no Effect of Working Capital on Consumer Behavior. Thus, the increase in working capital carried out as an effort for the company to expand, does not necessarily encourage consumers, in this case, investors, to invest their shares in the company.
- To test Hypothesis 2, there is an Effect of Working Capital on Sales Turnover. Thus, the increase in working capital carried out as an effort for the company to expand can encourage investor confidence to invest further in the company, because it can develop the effectiveness of the company to sell more products to the public.
- To test hypothesis 3, there is no effect of production costs on consumer behavior. Thus, an increase in production costs carried out to improve quality does not necessarily encourage consumers, in this case, investors, to invest their shares in the company, because product prices will increase and burden consumers.
- For the results of hypothesis testing 4, there is an effect of production costs on sales turnover. Therefore, an increase in production costs to improve product quality in the future can encourage public confidence to purchase products from the company, because the products are considered to be of higher quality and better for consumption.
5.2 Recommendations
Researchers provide advice to investors and the public as practical advice as follows:
- There is an influence of Working Capital on Sales Turnover, which means that the development of business capital is an indicator that the company is developing, which can increase its operational capacity. This can influence increasing sales turnover, so that it can be an indicator that the company is carrying out production that is more effective and marketing development.
- There is an Influence of Production Costs on Sales Turnover, which means that the development of production costs owned by the company can encourage more significant sales turnover, which tell that an increase in production costs can mean that the company invests in products with more excellent quality, so that it can increase consumer confidence in the product.
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