Application of Target Costing and Performance Analysis: Evidence from Indian Automobile Industry
Abstract:
Purpose: The manufacturing companies must keep attention over challenges and for the moment of adopt technology and practices instead of observation of competition amongst competitor companies.To create automobile business successful in India, companies are essential to adopt better cost accounting techniques to minimize cost of products and service costs.
Design/methodology/approach: This research investigates the application procedure of Target Costing (TC) in automobile companies in India. This study employed Target Costing as a dependent variable while Profitability; Growth; Net Tangibility Assets (NTA); EPS and Firm Size are independent variables. The study adopted convenience sample of top ten automobile companies listed on BSE of India and panel data has covered from 2014-15 to 2018-19 years. Data was analyzed through using statistical techniques of descriptive statistical analysis, Pearson’s Correlation, Simple Regression and Multiple Regression analysis and using the SPSS.
Findings: The result of the target costing impact on profitability has reported by Pearson’s correlation result shown a negative relationship. Similarly, Target costing impact on Return on sales examined by simple regression analysis and revealed that there is positive correlation. Finally, Target costing impact on financial performance examined by multiple regression results revealed that there is positive correlation with Revenue from Operation; Profitability; Return on Sales (ROS) and Growth, while negative correlation revealed by Margin from Operation; ROA; Net Tangibility Assets(NTA); EPS and Firm Size.
Originality/value: Target Costing has been identified as a popular technique to accomplish automobile company’s goals. Target costing consist exclusive approach to decide target price for the product and services. Target Costing ensure that new product price would be competitive in the market with substantial quality of products and services. This research investigates the application procedure of Target Costing (TC) and examined financial performance of Indian Automobile companies.
1. Introduction
Business environment twisted through the transformation, globalization and exploitation of competence and scenario controlled over the product operation’s life cycle of the companies. Additionally, new competitors are entering into the market because attracted by the upshot markets and escalating customer centric positions which have enormous multifaceted today’s business environment. Firms intend to implement modern production scheme as a result of changes in productivity technology. Therefore, traditional costing methods are inadequate to obtain accurate cost information for encounter the competition and sustain development of the organization. In the direction of achieve the goals of the business require accurate cost information and appropriate cost management are vital elements to become successful business enterprise and to avoid the augmented competition of business organizations. Currently, modern methods of cost accounting techniques comprise of progressive and exploratory approach to reduce cost of production and operation cost. Consequently, cost accounting keeps on established various modern methods, beyond which one of the significant cost accounting techniques is Target Costing (TC).
Target costing is a strategic cost accounting technique and the application of this technique emerged in Japanese manufacturing firms during the 1960’s( Kato, 1993 and Tani et al., 1994).Nonetheless, this technique merely not using Japanese manufacturing companies which has been broadly executed by other countries. Target costing is a valuable and resourceful technique; it has a wide- ranging tactic aimed at controlling costs and managing costs. Moreover, the application of this method in manufacturing sector to reduce productivity costs through sustaining quality starting from product proposal, product development and research, product scheduling because these plays a very significant character in the manufacturing product and development as well deciding modest price of the product and reaching the target profits (Jrirh, 2011).
Cost accounting has been innovated diverse methods and practices, the most tremendous method of which is target costing because the main goals of the business organizations to hold effort in competitive business environment for survive in the long term. The dire need is to attempting those practice and techniques that sustenance to their financial existence in the international competitive market. Consequently, automobile industry in India has various challenges amongst them one of the foremost circumstances is there is no progressive growth of sales since last two years. Thus, the automobile companies need to reduction in manufacturing costs through reduce pre-production costs in other expanses including Research and Development (R&D), manufacturing design, executing planning phases, with the regards to obtain additional costs saving.
2. Review of Literature
Target costing is an extensive model and which has been defined by many categories in the literature. Target costing method was initially developed in Japanese car manufacturing companies under the suitable name of Genkakikaku or Ginka Kikaku and became illustrious in accounting literature in the 1990s (Monder and Hamad, 1991; and Nicolini et al., 2000). The opinion of Ewert and Ernst (1999) stated about target costing as a strategic management accounting system because which can manage the product costs. According to Ballard (2008) emphasized that target costing as discussion amongst acceptable cost and expected cost. In the words of Ahmed, Cullen & Dunlop (1997) confirmed that the main intention of target costing is to attempt at the entire potential for reduction of production cost while designing new product.
Afonso et al.,(2008) in their research investigated that success of new product development depend on time to market and implementation of target costing. As well their research found that companies can achieve profit through implementation of target costing and minimize the supply time for distribute the product to modest markets. Therefore, the companies can setup time duration for supplying new products through lower costs and advanced quality of products by reducing manufacturing time to development of new product. In addition, Target costing can contribute for manufacturing new product with reasonable productivity control cost and provide better quality of product (Cooper and Chew, 1996). In the opinion of Dekker and Smdt,2003; Guilding et al., 2000; Cooper and Slagmulder, 1999 emphasized that the practice of target costing can determine cost of new product and is calculated as a result of subtract the expected profit margin from privileged market price of the product.
According to Ellarm (2006) Target Costing is significant cost accounting method for supporting manufacturers on the whole efforts to keep on cost competition whereas possible to apply standards and prerequisite demanded by customers. Fridh & Borgernas (2003) stated in their research, target costing is a product development procedure that facilitates to ascertain product cost resulting from product target price and afterward maintain the backward works of product plan and production process. In the opinion of Lockamy & Smith (2000) and Shank & Fisher (1999) target costing possibly will generate as a result while upward latest products, reduce cost of production in the course of maximum utilizing entire resources together with inclusive supply chain. Moreover, Target Costing makes use of price information from the prevailing market in order to ascertain product cost (Zengin and Ada, 2010).
Furthermore, Pierce (2002) emphasized that the target costing method must need complete information process and cross functional participation. In the opinion of Ansari et al (1997) states that the target costing is a market determined system, so that the consumers opinions are paramount significant and then consider into the account during the complete process. Therefore, there is a need to understand the consumer requirement and assess the competitor’s strategy and as a result must be effective to meet that requirement is essential. Target costing facilitate in manufacturing the new product determined in terms of quality, costs and performance (Cooper and Chew, 1996). N.Narsaiah (2018) employed target costing technique for Indian Railways and invented that in his research Target costing is not merely determine the price of Indian railways services because it is influenced with other factors like as population size, geographical factors and government subsidy policies to the customers.
Previous research studies does not employ target costing techniques to analysize cost leadership and determine performance of the companies. Therefore, this research paves the way and overcome the limitation of the previous research.
3. Theoretical Framework of Target Costing
Target costing is a strategic cost accounting technique uses for administration of a production and cost control which is relevance from the commencement of the production life process to maximize the products profitability. There are numerous definitions for target costing, the majority of which described with the intention of target costing is a practice employ in a cutthroat business market toward reduce primary costs and attain the expected profit margin. In a major definition, explained about target costing is an efficient system to determine cost of product for a chosen product with accurate quality and performance is to be estimated in order to that the estimated profit achieve from the estimated sales price (Jalali Naini et al.,2010).
As stated in earlier, Target costing is cost and management accounting technique its most important goal is to be minimize costs, although these technique main objective is assist in product development process in the direction of monitor lower cost, superior quality of product, consumers satisfaction and product launch at the right time in the market as per demand. Therefore, target cost works as a comprehensive business technique to accomplish organization objectives through innovative capable product (AL-Matarneh,2008; Jayeola & Onou, 2014).Target costing is a systematic approach which can ascertain the product cost based on the business achieve target profits through the sales of products. Target costing can achieve the product cost while product price is decided on the basis of competition.
Companies are very essential to plan for survive in the competition environment; therefore companies have to be expert in launching and promoting their product. Therefore, product quality and performance with accordance of consumer demand and companies are attempt to supply accordance with consumer satisfaction whereas companies are required to achieve expected return on their sales and making profitability business. First and foremost significant characteristic of target costing is the development and design of products which satisfy the consumer demand despite the fact that it can assists to the companies in reach their goals.
Target costing main focus on product price and which is also most affordable price to customer in privileged market. This scenario also put emphasis on consumer satisfaction through a product with lower cost and higher quality is possible to be produced and this goal is not realizable except that contribution and attentiveness of total departments of an organisation particularly supervise and controlling the cost of production prior to happening by the cost department. The application and practice of target cost method is possible to be relevant for each business organisation but requires several prerequisites environment including of well-established market research department through specialist, inventive employees and support from the top level management. Moreover, target cost can ascertain accurate cost of production and services.
4. Application of Target Costing Stages
The application of target costing should pursue throughout several stages, these process must start before the inauguration of the product and manufacturing stage follows by construct the plan and design. Subsequently, need to make the efforts for successful progress throughout the following stages which identified as the life-cycle of the product and there is no need to scare about the product features and quality. There is required stages to application of the target costing can be separated as follows (Margaret L. Gagne & Richard Discenza,1995; Sarokolaee, 2012; Dimi & Simona,2014 and Al-Adwan et al.,2018):
1. Determine the sales price for new product and subsequently investigate the market for projected sales volume and then set up target profit.
2. Ascertain the target cost through reduction the profit from the sales price.
3. Execute practical cost investigation for single and multiple process of product.
4. Ascertain the expected cost of the product.
5. Comparative analysis of expected cost by target cost.
6. When expected cost exceeds target cost and then replicate cost analysis to minimize expected cost.
7. Construct the ultimate decision for launching the product after estimation of target cost.
8. Administrate the production cost during the production stage and minimize the total cost through all possible approach.
5. Objectives of the Research
Each and every successful business organization must sustain competitive environment, which are associated to exclusive strategies and strategic cost management can supervise the success of the business organization during the long term. According to Naser, (2010) and Zengin & Ada, (2010) stated that target costing prime intention is to improve profitability, process, better production, reliable price, coordination between departments with marketing demand. Therefore, the prime objective of the research is to investigate the impact of Target costing application for automobile industry in India during the study. The study constitutes the following secondary objectives are:
1. To explore the application procedure of Target costing in Automobile Industry by theoretical model.
2. To investigate the target cost impact on profitability of automobile companies during the study period.
3. To investigate the automobile companies strengthen of Return on Sales (ROS) and competitiveness in the examination of cost leadership by target costing amongst the companies in India over the study period.
4. The study investigates the impact of target costing on overall financial performance of automobile industry.
6. Hypotheses of the Research
To achieve the research objectives, the study attempt to examine the following hypotheses:
Ho1 : To investigate for there is no significant correlation between target costing and profitability of automobile companies in India.
Ho2 : To investigate for there is no significant impact of target costing on Return on Sales (ROS) to assess competitiveness in the examination of cost leadership of automobile companies in India over the study period.
Ho3 : To investigate there is no significant impact of target costing on the financial performance of the automobile companies in India during the study period.
7. Research Methodology and Data Analysis
The main objective of this research is to investigate performance of automobile companies in India with application of target costing. This research is the empirical investigation as a result of employ target costing as the cost accounting technique because it is a massive accepted and application method in terms of production development, operations and supply chain management. In the opinion of Ellarm, (2006) emphasized that target costing is a legitimate and more precious approach to strengthen the context of awareness whereas conventional empirical analysis are unable to emphasize on the context to trace the real picture.
The sample of this research is consider as to cover of listed on Bombay Stock Exchange (BSE) of Indian Automobile companies as on 31 December 2019. The sample of the companies was selected based on the convenience sample and namely of companies are: (i) Ashok Leyland Limited; (ii) Bajaj Auto Limited;(iii) Eicher Motor Limited; (iv) Escorts Limited; (v) Force Motors; (vi) Hero Motocorp Limited; (vii) Mahindra & Mahindra Limited; (viii) Maharashtra Scooters Limited (MAHSCOOTER); (ix) Maruti Suzuki India Limited; (x) Tata Motors Limited. The sample of the selected companies also represented for top most market capitalization of Indian Automobile companies.
The sample of the research consist cross-sectional data of 10 selected automobile companies listed on the BSE in India. The data sourced from expertise which is based on the electronic data processing and maintained by individual companies. The research covers the panel data from 2014-15 to 2018-19 financial years. This research utilized financial reports of the selected companies on the source of convenience for 5 years. The selected companies which did not maintain comprehensive records on the variables were used in this research. Inferences are drawn on the basis of collected data processed, analyzed and interpreted make use of SPSS. The research covers of the 5 years data for each and every variable per selected companies in order to derive results and research examine structural changes if any.
The research adopted descriptive statistic, correlations and regression analysis statistical techniques for examine the automobile company’s data. The research examines the variables results authentication through employ descriptive statistical analysis. The first and foremost hypothesis approach of the study is examined through employ of pearson’s correlation test is employed to investigate in support of multicollinearity of the variables and which is based on the estimation of target costing and profitability of the automobile companies in India. The second hypothesis approach of the research is examined through employ of simple regression analysis test to measure, investigate and estimate the association amongst the variables to determines the strengthen of the companies competitiveness in cost leadership. Furthermore, third hypothesis approach of the research is examined by multiple regression analysis to study the financial performance of the automobile companies in India during the study period.
8. Explanatory Variables
The research is observed the data based on dependent and independent variables they are:
(a) Target Costing: According to Tanaka et al.(1993) stated in their research that Target costing can setting up by three methods, they are subtraction method; addition method and integrated method. Target costing can achieved through the subtraction method, significant factors are recognized by target costing particularly price determined by competitive companies. However, target costing can be ascertained by applying the following formula:
Target Costing = Selling Price - Desired Profit
Besides, addition method emphasize on the company’s internal factors and competences such as technology adoption, production system, supply of the products to customers, production size and strategic decisions of the company. Moreover, integrated method is the combination of the subtraction method and addition method.
(a)Profitability (PROFT): Profitability is the monetary gain which is arise when the sum of business operation income more than the sum of business expenditure including depreciation and taxes require to cover from such profit. Profitability benefit will distribute amongst the shareholders on the basis of their number of shares and rights. Profitability is estimated through the Earnings Before Interest and Taxes (EBIT) divided by Total Assets (EBIT/ Total Assets). Moreover, other estimates consider into account of like Return on Assets (ROA) and Return on Sales (ROS).
(b) Growth (GROW): Companies constitute more development opportunities for enhance the abilities of companies which are relatively expansion of the existing business, develop the new product, replacement of old assets with new assets, merger and acquisition of business. Companies indicated with fantastic growth rate option and this evidence shows that of higher strength of cash flows, this scenario motivated to companies to reduce the debts. Growth rate is estimated by the percentage changes in gross total assets.
(c) Net Tangible Assets (NTA): Tangible assets are the possessions of a business organisation that consist in the physical form (Example: Land, Building, Plant & Machinery, Materials and office equipments). Tangible asset value is used to calculate in this research by the formula is that the total assets of the company minus intangible assets and subtract total liabilities.
(d)Earnings per Share (EPS): Earnings per share refer to the amount of money received on each share of investment, while total profits are distributed at the end of the financial year to the outstanding shares. Earnings per share also describe as net income per share and it is also reflects how profitable of a company on the basis of outstanding shares. EPS is calculated in this research by subtracting preference share holder dividend from net profit and dividing by the total number of outstanding shares.
(e) Firm Size (SIZE): Conglomerate companies have more diversification option and secure cash flows and profitability. Financial risk of the large companies on the account of defaulters is very smaller proportion distinguished to small size companies. Firm size is estimated in this research by natural logarithm of the company’s total assets divided by natural logarithm of sales.
9. Application Procedure of Target Costing in Automobile Industry
Target Costing application in manufacturing industries have been followed by diverse procedures stages, United States firms developed system had highlighted on association amongst suppliers management and product design stages plays significant role in the Target costing practice. Moreover, later Japanese system in addition to the US firms system highlighted cost and management accounting system (Cooper & Slagmulder, 1999). Ellram (2006), described for application of target costing procedure divided into six stages in manufacturing industry. However, Target costing application procedure in automobile industry as follows (See Figure 1).
10. Results Analysis and Discussion
Table 1 represents the descriptive statistics analysis of related variables of this research. Statistical results revealed that there is an enormous variation in the minimum and maximum values of each variable of revenue from operations; margin from operations; target costing; Growth; Net tangibility assets; and EPS. Whereas profitability; return on assets; return on sales; and Firm Size has reported less variation between minimum and maximum values. Moreover, inferences were drawn from Mean statistic values of revenue from operation and target costing had reported highest mean values of 25058.93 and 23150.12 respectively and lowest Mean values are registered by return on sales and return on assets values showed 14.9264 and 14.4159 respectively. In addition, the mean value of the entire variables of the study revealed that there is no consistent average of natural logarithm for each values of variable.
Similarly, very higher standard deviation of variables of the study confirm that privileged dispersion or make wider data series for revenue from operation; target costing; net tangibility assets and margin from operation revealed highest values of 22536.77, 21140.67, 9269.85 and 2433.37 respectively. While lowest value 12.45 and 17.33 reported by return on assets and profitability respectively. Therefore, the descriptive statistical results concluded from the statistical results of the sample companies during the research period revealed that target costing and performance examination variables were fluctuating very extremely(See Table 1).
|
Minimum |
Maximum |
Mean |
Std. Deviation |
Variance |
Skewness | ||
Statistic |
Statistic |
Statistic |
Std. Error |
Statistic |
Statistic |
Statistic |
Std. Error | |
Revenue from Operation |
29.24 |
83026.50 |
25058.93 |
3187.18 |
22536.77 |
507906396.57 |
.804 |
.337 |
Target Costing |
15.10 |
75525.90 |
23150.12 |
2989.74 |
21140.67 |
446928017.62 |
.785 |
.337 |
Margin from Operation |
-4739 |
7722 |
1908.81 |
344.13 |
2433.37 |
5921292.94 |
.279 |
.337 |
Profitability |
-7.96 |
59.88 |
20.0427 |
2.45 |
17.33 |
300.61 |
.607 |
.337 |
Return on Assets |
-9.49 |
42.68 |
14.4159 |
1.76123 |
12.45 |
155.09 |
.488 |
.337 |
Return on Sales |
-13.06 |
86.21 |
14.9264 |
2.98874 |
21.13 |
446.62 |
2.38 |
.337 |
Growth |
-4.10 |
1848.28 |
52.5748 |
36.70 |
259.54 |
67364.18 |
7.03 |
.337 |
Net Tangibility Assets |
236.44 |
31742.19 |
10046.54 |
1324.26 |
9269.85 |
85930236.38 |
.714 |
.340 |
EPS |
-15.00 |
753.37 |
128.92 |
23.59436 |
166.83 |
27834.68 |
2.20 |
.337 |
Firm Size |
.24 |
224.77 |
9.7395 |
5.37736 |
38.02 |
1445.79 |
4.67 |
.337 |
|
Minimum |
Maximum |
Mean |
Std. Deviation |
Variance |
Skewness | ||
Statistic |
Statistic |
Statistic |
Std. Error |
Statistic |
Statistic |
Statistic |
Std. Error | |
Valid N (list wise) | 50 | 50 | 50 | 50 | 50 | 50 | 50 | 50 |
11. Test of Hypotheses Results and Discussions
Table 2 represents the Pearson’s correlation result of target costing and profitability shown that there is a negative relationship between variables. The result of statistical analysis indicated negative relationship between the target costing and profitability of automobile companies India and correlation of coefficient value exhibited is -0.073. This scenario revealed that as target costing increases in the study period and that would cause a significant impact on the profitability of the companies. Statistical inferences were drawn from the Pearson’s coefficient of correlation confirm that profitability of the companies are decreased during the study period. The significance of (2-tailed) calculated value is reported by 0.615 and which indicated that this statistical value is more than the critical value of 0.05.
Furthermore, Pearson’s correlation of coefficient concluded that there no statistically significant correlation between target costing and profitability of automobile companies in India. Additionally, null hypothesis of the research is accepted because results shown impact of Target costing on profitability of automobile companies in India. Therefore, ultimate conclusion of the Pearson’s correlation determined that target costing have a great impact on profitability of the automobile companies in India (See Table 2 to 2.1).
| Target Costing | Profitability | |
Target Costing | Pearson Correlation | 1 | -.073 |
Sig. (2-tailed) |
| .615 | |
Sum of Squares and Cross-products | 21899472863.390 | -1309616.668 | |
Covariance | 446928017.620 | -26726.871 | |
Profitability | Pearson Correlation | -.073 | 1 |
Sig. (2-tailed) | .615 |
| |
Sum of Squares and Cross-products | -1309616.668 | 14729.988 | |
Covariance | -26726.871 | 300.612 |
| Mean | Std. Deviation | N |
Target Costing | 23150.123 0 | 21140.6721 2 | 50 |
Profitabilit y | 20.0427 | 17.33817 | 50 |
Table 4 represents the simple regression analysis results of Target costing and Return on Sales (ROS) of the automobile companies in India. The research results indicated that there is a positive correlation amongst Target costing and Return on Sales (ROS). The research confirmed relationship by the significant and size of R is reported 0.416. Moreover, from the regression analysis estimated on Table 4, R-squared revealed that 0.173 or 17.3 per cent significant variation between the target costing and return on sales. As this results indicated that with affect on research by target costing occupy alone by 17.3 per cent and remain 82.7 variation by the other dependent variables and this factors were not incorporated in this research model.
Furthermore, Table 6 represents of coefficient analysis of Un standardized coefficient of β indicated by -415.90 per cent decreased in the return on sales with holding variable of target costing constant. The results of statistical analysis concluded that Return on Sales (ROS) predicted target costing would be 415.90 per cent lower. The variable return on sales indicated with the value of 0.003 is significantly different from 0, because the p- value is less than 0.05. This result indicated that doesn’t have impact of target costing on Return on Sales (ROS) of Automobile companies in India. However inferences were drawn from statistical analysis is that selected automobile companies are administrating their Target costing in appropriate approach, therefore, there is no significant impact of target costing on Return on Sales (ROS) over the study period and finally accept the null hypothesis of the research.
The Durbin Watson statistic test is examined the correlation (time series data) or auto-correlation (panel data) in research model. The results revealed by the Durbin Watson test is 0.268 and this statistical value is more than 0 but less than 2, this indicated that the present research data has the evidence of positive auto-correlation amongst variables. ANOVA test is a formal healthiness of test which can assist to examine the linearity of research model. Regression analysis criteria emphasize that the model must be linear and the result presented in table 5, F test suggest that null hypothesis would not reject. As a result, this study revealed that this research model is properly specified. F change value is reported that very significant value of 10.031 probability thus, this F test indicated that there is no significant impact of target costing on return on sales.
Moreover, Table 6 represent the statistical results of co-efficient analysis at 95% level of confidence interval, the t-statistics value revealed by -3.167 while p- value of t-statistic significance is reported by 0.003.Therefore, calculated value is less than the significance value hence, provide evidence that there is no significant impact of target costing on Return on Sales (ROS) of automobile companies in India (See Table 4 to Table 8).
Model Summary | ||||||||||
Mod el | R | R Squa re | Adjust ed R Square | Std. Error of the | Change Statistics | Durbi n- Wats on | ||||
R Squa re | F Chan ge | df 1 | df 2 | Sig. F Chan ge | ||||||
Estimat e | Chan ge | |||||||||
1 | .41 6a | .173 | .156 | 19426.1 19 | .173 | 10.03 1 | 1 | 4 8 | .003 | .268 |
a. Predictors: (Constant), Return on Sales | ||||||||||
b. Dependent Variable: Target Costing |
ANOVA | ||||||
Model | Sum of Squares | df | Mean Square | F | Sig. | |
1 | Regressio n | 3785514821.953 | 1 | 3785514821.95 3 | 10.03 1 | .003 b |
Residual | 18113958041.43 7 | 4 8 | 377374125.863 | |||
Total | 21899472863.39 0 | 4 9 | ||||
a. Dependent Variable: Target Costing | ||||||
b. Predictors: (Constant), Return on Sales |
Coefficients | |||||||||||
Model | Un standardized Coefficients | Standardized Coefficients | t-Statistic | Sig. | 95.0% Confidence Interval for B | Correlations | |||||
B | Std. Error | Beta | Lower Bound | Upper Bound | Zero-order | Partial | Part | ||||
1 | (Const ant) | 29358.03 6 | 3374.80 6 | 8.699 | .00 0 | 22572.53 | 36143. 5 | ||||
Return on Sales | -415.902 | 131.315 | -.416 | -3.167 | .00 3 | -679.92 | -151.87 | -.416 | -.416 | -.416 | |
a. Dependent Variable: Target Costing |
Coefficient Correlations | |||
Model | Return on Sales | ||
1 | Correlations | Return on Sales | 1.000 |
Co variances | Return on Sales | 17243.634 | |
a. Dependent Variable: Target Costing |
Residuals Statisticsa | |||||
| Minimum | Maximum | Mean | Std. Deviation | N |
Predicted Value | -6498.6060 | 34788.3828 | 23150.1230 | 8789.50536 | 50 |
Residual | - 25340.83789 | 49794.32031 | .00000 | 19226.87216 | 50 |
Std. Predicted Value | -3.373 | 1.324 | .000 | 1.000 | 50 |
Std. Residual | -1.304 | 2.563 | .000 | .990 | 50 |
a. Dependent Variable: Target Costing |
Table 9 represents the multiple regression analysis of Target costing and financial performance of the selected and listed on BSE automobile companies of India. The regression results revealed that positive relationship amongst Target costing to independent variables of Revenue from operation; Margin from operation; Profitability, ROA; ROS, Growth; EPS, Net Tangibility Assets (NTA) and Firm SIZE. The statistical analysis of multiple regression analysis estimated on Table 9 showed the R- square about 100% and it is authenticated that there is no variation amongst research explanatory variables.
Furthermore, the statistical analysis of co-efficient revealed on the table 11 with theTarget costing to the explanatory independent variables has positive relationshipthrough the Un standardized Co-efficient of β value with Revenue from operations;Profitability; Return on Sales (ROS) and Growth by 1.000; 3.558; 9.422 and and 4.211 respectively and also p-value shown by 0.000 for the respective of all the independent variable. Therefore, the positive co-efficient relationship amongst Target costing and independent variables results confirm that the multiple regression results statistically significant. While the negative relationship revealed with the Un standardized Co- efficient of β value with the Target costing to the Margin from Operation; Return on Assets (ROA); Net Tangibility Assets (NTA); EPS and Firm Size by -1.000; -5.642; - 2.855; -1.830 and -4.702 respectively and also p-value shown by 0.000 for the concerned of all the research independent variables, consequently the negative relationship amongst Target costing and independent variables results confirm that the multiple regression results statistically insignificant with such variables.
The Durbin Watson statistic test is examined the correlation (time series data) or auto-correlation (panel data) in research model. The results revealed by the Durbin Watson test is 0.867 and this statistical value is more than 0 but less than 2, this indicated that the present research data has the evidence of positive auto-correlation amongst variables. ANOVA test is a formal fitness of test which can assist to examine the linearity of research model. Regression analysis criteria emphasize that the model must be linear and the result presented in table 10, F test suggested that null hypothesis would not reject. As F-Statistical test is exhibited about this research model is properly specified.
However, the research results investigated with the Target Costing impact on Revenue from Operation; Profitability; Return on Sales (ROS) and Growth established positive correlation, while through the other independent variable confirmed negative correlation by Margin from Operation; ROA; Net Tangibility Assets; EPS and Firm Size. Although, the Target Costing could have enormous impact on the selected companies business operations during the study period because statistical results impart with mixed results (See Table 9 to table 12).
Model Summary | ||||||||||
Model |
R |
R Square | Adjusted R Square | Std. Error of the Estimate | Change Statistics | Durbin - Watso n | ||||
R Squar e Chang e | F Chang e | df 1 | df 2 | Sig. F Chang e | ||||||
| 1.000 | 1.00 | 1.00 | .0000 | 1.000 | . | 9 | 39 | .000 | .867 |
a | 0 | 0 | 0 |
|
|
|
|
|
| |
a. Predictors: (Constant), Firm Size, Net Tangibilty Assets, EPS, ROS, ROA, Margin from Operations, Growth, Revenue from Operation, Profitability | ||||||||||
b. Dependent Variable: Target Costing |
ANOVAa | ||||||
Model | Sum of Squares | df | Mean Square | F | Sig. | |
1 | Regression | 21867425268.563 | 9 | 2429713918.729 | . | .b |
Residual | .000 | 39 | .000 |
|
| |
Total | 21867425268.563 | 48 |
|
|
| |
a. Dependent Variable: Target Costing | ||||||
b. Predictors: (Constant), Firm Size, Net Tangibilty Assets, EPS, ROS, ROA, Margin from Operations, Growth, Revenue from Operation, Profitability |
Coefficients | ||||||
Model | Un standardized Coefficients | Standardized Coefficients | t-Statistics | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | -5.034E- | .000 |
| -3.597 | .001 |
|
| 12 |
|
|
| |
| Revenue | 1.000 | .000 | 1.067 | 18728701641934296.00 | .000 |
| from |
|
|
|
|
|
| Operation |
|
|
|
|
|
| Margin | -1.000 | .000 | -.114 | -2274898973206912.00 | .000 |
| from |
|
|
|
|
|
| Operations |
|
|
|
|
|
| Profitability | 3.558E-12 | .000 | .000 | 7.649 | .000 |
| ROA | -5.642E- | .000 | .000 | -8.257 | .000 |
|
| 12 |
|
|
|
|
| ROS | 9.422E-13 | .000 | .000 | 12.202 | .000 |
| Growth | 4.211E-14 | .000 | .000 | 7.725 | .000 |
Coefficients | ||||||
Model | Un standardized Coefficients | Standardized Coefficients | t-Statistics | Sig. | ||
B | Std. Error | Beta | ||||
| Net | -2.855E- | .000 | .000 | -21.157 | .000 |
Tangibility | 15 |
|
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| |
Assets |
|
|
|
|
| |
EPS | -1.830E- | .000 | .000 | -3.648 | .001 | |
| 14 |
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| |
Firm Size | -4.702E- | .000 | .000 | -8.582 | .000 | |
| 13 |
|
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| |
a. Dependent Variable: Target Costing |
Residuals Statisticsa | |||||
| Minimum | Maximum | Mean | Std. Deviation | N |
Predicted Value | 15.1000 | 75525.8984 | 23264.4937 | 21344.11769 | 49 |
Residual | .00000 | .00000 | .00000 | .00000 | 49 |
Std. Predicted Value | -1.089 | 2.449 | .000 | 1.000 | 49 |
Std. Residual | . | . | . | . | 0 |
a. Dependent Variable: Target Costing |
12. Conclusion
Target costing application for automobile companies is deliberate as the modern approach to shrink strategic costs that facilitate to the development of companies and achieve equivalent benefits over the competitors in market. This scenario is potential for automobile companies with the establishment of cost center and accomplish persistent growth of companies for survive in the competitive market. This research investigated results of automobile companies by application of target costing as a cost accounting technique to ROS and financial performance of selected companies of India.
The research major finding through descriptive statistics of explanatory variables by standard deviation revealed very wider dispersion for revenue from operation; target costing; net tangibility assets and margin from operation, whereas lowest dispersion revealed by return on assets and profitability. The research determined the significance relationship between Target costing and Profitability of automobile companies in India results indicated by Pearson’s correlation that there is a negative relationship between variables. In additionally, Pearson’s correlation determined that target costing have a great impact on profitability of the automobile companies. Besides, simple regression analysis revealed a positive correlation between Target costing and Return on Sales (ROS) of the automobile companies in India. Also, Return on Sales (ROS) predicted target costing would be 415.90 lower than for return on sales.
Moreover, research results of multiple regression analysis of Target costing to financial performance of the selected automobile companies revealed that positive relationship by the Un standardized Co-efficient of β value with Revenue from operations; Profitability; Return on Sales (ROS) and Growth. Whereas the negative relationship revealed with the Un standardized Co-efficient of β value with the Target costing to the Margin from Operation; Return on Assets (ROA); Net Tangibility Assets (NTA); EPS and Firm Size. The results of target costing and financial performance revealed that the significant association amongst variables. The scope of the application of target costing and financial performance of automobile companies in India with R-Square value of 1.000 and p value 0.000.
13. Future Research
This research can be possible to further extend and examine the significant relationship among the target costing and different cost components of manufacturing and service sectors. Additionally, target costing techniques strength of character in achieve cost competitive advantages amongst competative companies by comaring costs with employ target costing at various stages of manufacturing and service sector.
Appendix 1: Selected Companies Target Costing and Financial Analysis
Name of the Company | Revenue from Operation | Margin from Operations | Target Costing |
Profitability | ROA |
ROS |
Growth | Net Tangibility | EPS | Firm Size | |
1 | Ashok Leyland Limited |
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| 2014-15 | 13,311.14 | 334.81 | 12,976.33 | 3.3219 | 2.55151 | 2.5152 | 3.931 | 2,610.99 | 1.2 | 1 |
| 2015-16 | 18,560.77 | 389.6 | 18,171.17 | 6.4706 | 3.05 | 2.099 | -4.0396 | 1946.36 | 1.37 | 0.68821 |
| 2016-17 | 19,741.58 | 1,223.08 | 18,518.50 | 9.4735 | 8.7113 | 6.1954 | 9.9134 | 5811.35 | 4.24 | 0.7111 |
| 2017-18 | 25,965.78 | 1,717.73 | 24,248.05 | 13.7619 | 9.9082 | 6.6153 | 23.4779 | 9631.5 | 5.87 | 0.6676 |
| 2018-19 | 28,614.03 | 1,983.20 | 26,630.83 | 13.7003 | 10.8821 | 6.9308 | 5.1222 | 9658.53 | 6.76 | 0.6369 |
2 | Bajaj Auto Limited |
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| 2014-15 | 21,103.93 | 2,813.74 | 18,290.19 | 37.8084 | 26.0437 | 13.3327 | 11.7751 | 10692.15 | 97 | 0.5119 |
| 2015-16 | 22,151.71 | 3,929.67 | 18,222.04 | 41.8143 | 29.6208 | 17.7398 | 22.7938 | 13177.26 | 135.8 | 0.5988 |
| 2016-17 | 21,373.52 | 3,827.56 | 17,545.96 | 31.1042 | 22.3128 | 17.9079 | 29.3028 | 16.989.48 | 132.3 | 0.8025 |
| 2017-18 | 24,700.30 | 4,068.10 | 20,632.20 | 30.0789 | 21.1608 | 16.4698 | 12.0706 | 19103.86 | 140.6 | 0.7783 |
| 2018-19 | 29,567.25 | 4,675.18 | 24,892.07 | 30.7768 | 21.4655 | 15.812 | 13.2916 | 21760.15 | 161.6 | 0.7366 |
3 | Eicher Motor Limited |
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| 2014-15 | 4,641.26 | 928.58 | 3,712.68 | 59.3829 | 41.6611 | 20.007 | 50.2777 | 1221.73 | 342.25 | 0.4802 |
| 2015-16 | 6,186.19 | 1,309.22 | 4,876.97 | 51.1328 | 36.1277 | 21.1635 | 62.5881 | 2307.37 | 482.45 | 0.5858 |
| 2016-17 | 7,037.97 | 1,560.02 | 5,477.95 | 41.0989 | 28.1578 | 22.1657 | 52.8807 | 3889.18 | 573.75 | 0.7871 |
| 2017-18 | 8,957.51 | 1,712.91 | 7,244.60 | 33.9753 | 21.9754 | 19.1226 | 40.6914 | 5333.57 | 629.07 | 0.8701 |
| 2018-19 | 9,794.48 | 2,054.44 | 7,740.04 | 33.0573 | 21.6772 | 20.9754 | 21.5883 | 6947.47 | 753.37 | 0.9676 |
4 | Escorts Limited |
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| 2014-15 | 3,962.28 | 74.71 | 3,887.57 | 3.1472 | 3.4451 | 1.8743 | 1.0686 | 561.77 | 6.26 | 0.544 |
| 2015-16 | 3,456.05 | 89.38 | 3,366.67 | 4.4174 | 4.2977 | 2.5741 | -4.0972 | 600.44 | 7.49 | 0.5989 |
| 2016-17 | 4,078.19 | 160.44 | 3,917.75 | 12.5428 | 7.2714 | 3.9197 | 6.0941 | 640.55 | 13.43 | 0.539 |
| 2017-18 | 4,953.30 | 344.72 | 4,608.58 | 19.8618 | 13.4562 | 6.9011 | 16.1056 | 804.54 | 28.85 | 0.5128 |
| 2018-19 | 6,116.76 | 484.91 | 5,631.85 | 21.906 | 14.7288 | 7.8257 | 28.5132 | 1287.8 | 40.48 | 0.5313 |
5 | Force Motors |
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| 2014-15 | 2,335.13 | 101.36 | 2,233.77 | 6.3367 | 5.1407 | 4.2881 | 11.2761 | 236.44 | 76.93 | 0.8341 |
| 2015-16 | 3,031.35 | 179.42 | 2,851.93 | 10.8672 | 7.8217 | 5.8638 | 16.3403 | 326.25 | 136.17 | 0.7496 |
| 2016-17 | 3,037.95 | 179.92 | 2,858.03 | 9.0379 | 6.9195 | 5.8625 | 13.353 | 1138.2 | 136.55 | 0.8472 |
| 2017-18 | 3,392.37 | 146.95 | 3,245.42 | 7.9486 | 5.8335 | 4.2935 | -3.1209 | 1147.78 | 111.53 | 0.7359 |
| 2018-19 | 3,620.01 | 147.18 | 3,472.83 | 6.8341 | 5.1898 | 4.03 | 12.579 | 1222.71 | 111.7 | 0.7765 |
6 | Hero Motocorp Limited |
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| 2014-15 | 27,518.00 | 2,385.64 | 25,132.36 | 50.889 | 36.4702 | 8.6482 | 16.8121 | 2466.56 | 119 | 0.2371 |
| 2015-16 | 28,359.91 | 3,132.37 | 25,227.54 | 59.8769 | 42.6769 | 10.9526 | 12.1996 | 2824.52 | 156.86 | 0.2566 |
| 2016-17 | 28,169.54 | 3,377.12 | 24,792.42 | 46.0718 | 33.3995 | 11.8493 | 37.7681 | 5443.46 | 169.12 | 0.3547 |
| 2017-18 | 31,589.51 | 3,697.36 | 27,892.15 | 44.5595 | 31.4164 | 11.4716 | 16.3934 | 6630.31 | 185.14 | 0.3651 |
| 2018-19 | 33,124.53 | 3,384.87 | 29,739.66 | 38.9724 | 26.3268 | 10.0588 | 9.2467 | 7932 | 169.48 | 0.382 |
7 | Mahindra & Mahindra Limited |
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| 2014-15 | 38,391.61 | 3,321.11 | 35,070.50 | 12.6541 | 10.0808 | 8.5276 | 5.2933 | 19121.07 | 56.23 | 0.8459 |
| 2015-16 | 40,386.75 | 3,204.57 | 37,182.18 | 12.069 | 9.027 | 7.8399 | 7.7544 | 21372.91 | 53.05 | 0.8684 |
| 2016-17 | 43,378.93 | 3,643.39 | 39,735.54 | 11.8158 | 9.1156 | 8.2703 | 12.5881 | 25551.3 | 30.69 | 0.9072 |
| 2017-18 | 48,112.32 | 4,356.01 | 43,756.31 | 12.8696 | 9.1866 | 8.9472 | 18.6358 | 28942.58 | 36.64 | 0.9739 |
| 2018-19 | 52,960.80 | 4,796.04 | 48,164.76 | 12.0025 | 9.1011 | 8.9454 | 11.1359 | 31742.19 | 40.29 | 0.9828 |
8 | Maharashtra Scooters Limited |
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| 2014-15 | 69.86 | 54.76 | 15.10 | 17.2022 | 17.2022 | 78.3853 | 6.0075 | 252.26 | 47.91 | 4.5566 |
| 2015-16 | 117.15 | 101 | 16.15 | 29.9401 | 29.9401 | 86.2142 | 5.9717 | 311.99 | 88.37 | 2.8795 |
| 2016-17 | 29.24 | 13.07 | 16.17 | 0.2181 | 0.2181 | 49.0424 | 1848.2777 | 6552.49 | 11.43 | 224.771 |
| 2017-18 | 82.12 | 60.76 | 21.36 | 0.7441 | 0.7441 | 74.6955 | 25.4216 | 8225.27 | 53.16 | 100.378 |
| 2018-19 | 95.93 | 72.8 | 23.13 | 0.6346 | 0.6346 | 77.5565 | 42.2158 | 11323.22 | 63.7 | 122.203 |
9 | Maruti Suzuki India Limited |
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| 2014-15 | 48,605.50 | 3,711.20 | 44,894.30 | 20.3823 | 15.5381 | 7.4267 | 5.3889 | 13745.3 | 123 | 0.4779 |
| 2015-16 | 56,441.20 | 5,364.30 | 51,076.90 | 24.8441 | 17.9039 | 9.323 | 25.4442 | 17558.9 | 177.58 | 0.5207 |
| 2016-17 | 66,909.40 | 7,350.20 | 59,559.20 | 26.9819 | 19.9113 | 10.8035 | 23.2067 | 21722.2 | 243.32 | 0.5425 |
| 2017-18 | 78,104.80 | 7,721.80 | 70,383.00 | 26.2811 | 18.4431 | 9.6809 | 13.4185 | 23943.6 | 255.62 | 0.5249 |
| 2018-19 | 83,026.50 | 7,500.60 | 75,525.90 | 22.6082 | 16.2031 | 8.7195 | 10.5641 | 29127.8 | 248.3 | 0.5381 |
10 | Tata Motors Limited |
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| 2014-15 | 35,890.50 | -4,738.95 | 40,629.45 | -7.9584 | -9.4886 | -13.0568 | 0.4197 | 11339.86 | -15 | 1.376 |
| 2015-16 | 42,345.39 | -62.3 | 42,407.69 | 0.2749 | -0.1099 | -0.1454 | 13.4809 | 19759.55 | -0.18 | 1.3228 |
| 2016-17 | 43,340.62 | -2,429.60 | 45,770.22 | -3.9968 | -4.1264 | -5.4824 | 3.8857 | 18286.81 | -7.15 | 1.3285 |
| 2017-18 | 57,441.05 | -1,034.85 | 58,475.90 | -1.5991 | -1.7476 | -1.759 | 0.5673 | 16759.75 | -3.05 | 1.0064 |
| 2018-19 | 68,764.88 | 2,020.60 | 66,744.28 | 3.9385 | 3.3173 | 2.9198 | 2.8665 | 19286.72 | 5.94 | 0.8801 |
Source: Authors Compiled data