Developing the system of business performance analysis indicators of paper enterprises in vietnam

Nội dung text: Developing the system of business performance analysis indicators of paper enterprises in vietnam

1. DEVELOPING THE SYSTEM OF BUSINESS PERFORMANCE ANALYSIS INDICATORS OF PAPER ENTERPRISES IN VIETNAM M. Diep To Uyen dieptouyen@hvu.edu.vn, Hung Vuong University, Phu Tho province, Vietnam Dr. Nguyen Ngoc Quang nnq1966@gmail.com, National Economics University, Hanoi, Vietnam Abstract This study aims to develop a system of performance analysis indicators for Vietnam’s paper enterprises. The research results developed a system of 34 indicators analyzed according to the horizontal information analysis process of Brown (1996). The analytical indicators focus on economic efficiency but also refer to factors of social efficiency and ecological efficiency. At first, the study used a technique of in-depth interviews with 15 paper industry experts to discover new problems. Then, the study used EFA and ANOVA to analyze data from the survey of 206 Vietnamese paper enterprises of different sizes. Research results are the basis for proposing recommendations for Vietnam’s paper enterprises on the use of these analytical indicators. Keywords: efficiency, Vietnam’s paper enterprises, analytical indicators\ 1. Introduction Effective business is the goal during the operation of enterprises. Analysis of business performance has urgent meaning for the sustainable development of enterprises in the current competitive and global economy. The analytical criteria are considered useful when performance’s analysis has been verified with a number of specific purposes (Beaver (1966), George E. Pinches, Kent A. Mingo et al. 1973, Chen and Shimerda 1981). The system of analysis indicators will be more comprehensive when there is a combination of financial and non-financial indicators (Kaplan 1996, Kaplan 2001, Ittner and Larcker 2003). The system of business performance analysis indicators is not comprehensive if only analyzing the overall efficiency of enterprises. From the perspective of the internal value chain of the enterprise, the product will go through all the activities of the chain and for each activity the product will accumulate some value (Porter 1985). The main activities in the chain such as supply, production and consumption are linked. The output of this operation is the input of the next activity. Therefore, in addition to the overall 215
2. efficiency, it is necessary to analyze the efficiency of the stages in the business process as input - the production process - output - results. The Vietnam’s paper industry was formed very early, playing a very important role in the growth and development of the education, economics and social culture of the country. Although production has increased significantly so far, however, the profitability ratios of Vietnam’s paper enterprises in recent years tends to decrease, contributing a small contribution to the total national production value. The Vietnam’s paper industry is facing a big problem from its internal industry such as: high product prices, not meet the demand for quantity and quality, the product category is not diversified, the output of all kinds of products is not balanced. The paper production process will consume a lot of energy, so it depends on imported raw materials; heterogeneous and outdated production equipment has resulted in the paper production in Vietnam having high levels of pollution, causing significant impacts on people and the surrounding environment. Therefore, the business performance of paper enterprises is assessed not only in economic perspective but also with consideration of ecological efficiency. The view of efficiency is very wide and complex, but in this study, the author gives the following viewpoint of efficiency: “Business efficiency of an enterprise is an economic category, reflecting the ability to reach the intended goal through the use of real resources and maximizing the benefits of potential resources, is shown by comparing the correlation between the outputs with the inputs. Business performance of enterprises is a process of causal connection, the overall efficiency is generated from the business performance of different departments of the enterprise associated with the production and business process of the enterprise”. The theoretical model in this study is the Input - Process - Output model - Result (Brown 1996). Brown's model was officially born as a theoretical model to measure performance based on horizontal analysis of information, that is, focus on an organization's business process (Figure 1). Input Model - Process - Output - Brown's results are very useful because it highlights the difference when measuring inputs, processes, outputs and outcomes based on causal relationships. Brown took the illustration of baking to clarify this. Measuring the input of baking will involve the amount of flour, egg quality that is related to the quantity and quality of the input materials. Process measurement will involve oven temperature and baking time. Measurement output will be concerned with the quality of the cake, that is the quality of products or services created. Measuring the output will be related to the satisfaction of cake eaters (Brown 1996). 216
3. 2. Method After synthesizing previous studies on indicators of business performance analysis, the author has built a system of indicators for analyzing business performance, including indicators for analyzing department efficiency and indicators for general efficiency analysis with expected expectations of stakeholders in the analysis process. The system of proposed indicators includes 41 indicators, divided into 4 groups: Group of indicators to analyze the efficiency of input supply activities; Group of indicators to analyze the efficiency of production and business activities; Group of indicators to analyze the efficiency of consumption activities and indicators’ group analyzing the efficiency of overall operations. After that, the author started the process of experimental research with 2 phases: Qualitative research phase and Quantitative research phase. Qualitative research is carried out in the first stage of the research process of the indicator system to analyze the efficiency of business operations, to eliminate targets that most experts consider inappropriate or duplicated when based on business characteristics of Vietnam’s paper enterprises. Qualitative research techniques used are in-depth interviews (semi-structured). Experts participating in in-depth interviews are researchers and experts at the Research Institute for Paper Technology and Xenluylo, managers of paper enterprises The main content is interested in in-depth interviews around the system of 41 indicators to analyze the efficiency of business performance: What is the assessment of the appropriateness of the system of indicators of business performance analysis? What is the importance indicators of business performance analysis? What is the frequency of using indicators in the analysis? Quantitative research: The purpose of the quantitative research method in this step is to provide a complete system of indicators for analyzing business performance, 217
4. meeting the needs of information analysis of Vietnam’s paper enterprises. The scales selected from qualitative research results will be included in the survey to collect data on a wider scale. According to the survey data of the General Statistics Office of Vietnam in 2017, Vietnam has 2,485 paper enterprises of different types and sizes, often scattered or concentrated in industrial clusters and trade village clusters. The author will base on the requirement of a sufficiently reliable sample size for analysis based on the experience of previous studies to be able to use the appropriate method in this study. Specifically, with the method of exploratory factor analysis EFA, the sample size is at least 5 times the number of measurement variables. The results of qualitative research give 40 measurement variables, so the minimum sample size is 5x40 with 200 samples (Hair, Anderson et al. 1998). To ensure minimum collection of 200 samples, the author issued 280 survey forms. Sampling method in the study is convenient sampling in Yen Bai, Phu Tho, Vinh Phuc, Hanoi, Hung Yen, Bac Ninh and Thanh Hoa provinces. The form of the survey questionnaire is directly, via email and by phone. Variables used in the study are qualitative variables measured through Likert scale (5 options). Research question: Please give a view on the importance of indicators in analyzing business performance in units with 5 levels of selection: 1. Do not use, 2. Less use (once a year), 3. Periodically (every 6 months), 4. Regularly used (quarterly), 5. Very often used (monthly). The collected survey data will be cleaned of information, data entry and statistical analysis of sample description on SPSS 20 software. Then, the analysis steps are as follows: - Remove variables that are not reliable enough by Cronbach’s Alpha index and Corrected Item - Total Correlation. According to (Hair, Anderson et al. 1998) eligible variables are variables with Cronbach’s Alpha coefficient of 0.6 or higher, and according to (Nunnally and Bernstein 1978), the coefficient Corrected Item - Total Correlation is 0.3 or higher. Unqualified scales will be removed. - Exploratory factor analysis (EFA) to assess convergence value, discriminant value of scale. The method of extracting the principal component combines varimax rotation. Conditions for EFA analysis according to (Hair et al., 1998) are to meet the requirements: + Factor Loading> 0.5; + Index 0.5 ≤ KMO ≤ 1; + The Bartlett test has statistical significance (Sig. 50% 218
5. - Testing ANOVA to consider the difference in the indicator system between manufacturing enterprises and distribution enterprises, between enterprises of different sizes by comparing the weighted mean among enterprises. 3. Results Research shows that the suitability of the division of group indicators, after adjusting based on qualitative results, the indicator system has changed from 41 initial indicators with 38 indicators as shown in Table 1: Table 1. Indicator system for analyzing business performance of Vietnam’s paper enterprises after qualitative research Encode Indicator system for analyzing business performance 1. Group of indicators to analyze the efficiency of input supply activities CTDV01 Efficiency in providing quality materials CTDV02 Efficiency in providing materials types CTDV03 Coefficient of capacity to supply energy for paper production CTDV04 Coefficient of water supply capacity for paper production CTDV05 The degree of completion of the indicator "average purchase price per unit of material or goods each type” CTDV06 Time to ensure materials or goods for paper production and business activities CTDV07 Procurement costs per unit of raw materials supplied CTDV08 Innovation coefficient of fixed assets CTDV09 Coefficient of fixed asset equipment for paper production per a worker CTDV10 Cost rate of chemical additives CTDV11 Rate of trained workers CTDV12 The average training time per employee 2. Group of indicators to analyze the efficiency of production and business activities CTSX13 Rate of consumption of raw materials / energy / water per unit of finished paper CTSX14 Average labor productivity CTSX15 Coefficient of using existing equipment and machinery 219
6. Encode Indicator system for analyzing business performance CTSX16 Average productivity of one hour of machine CTSX17 The rate of broken paper products CTSX18 Rate of cost repairing and maintaining the equipment. 3. Group of indicators to analyze the efficiency of consumption activities CTDR19 Ratio of net revenue compared to cost CTDR20 Cost for 1,000 VND of paper products CTDR21 Efficiency ratio of sold goods’ cost CTDR22 Efficiency ratio of sales’ cost CTDR23 Efficiency ratio of enterprise management’s costs 4. Group of indicators to analyze the efficiency of overall operations CTKQ24 The add value per each employee CTKQ25 Performance of using materials CTKQ26 Energy, water consumption productivity CTKQ27 Production capacity of fixed assets CTKQ28 Profitability ratio of fixed assets CTKQ29 Return on investment (ROI) CTKQ30 Return on equity (ROE) CTKQ31 Return on assets (ROA) CTKQ32 Number of asset revolutions CTKQ33 Return on revenue CTKQ34 Number of inventory rotations CTKQ35 Time for one inventory rotation CTKQ36 Income of a stock CTKQ37 Contribution index of enterprises for the state budget CTKQ38 Index of environmental improvement (Source: Author's investigation and synthesis) In the research sample, number of operation’s years of the business paper ranged from 1 year to 57 years, in which, the number of enterprises with less than 10 years of operation accounted for 46% (95 enterprises), the number of enterprises 220
7. operating from 10 to less than 15 years accounted for 41,7% (86 enterprises) and the number of enterprises operating over 15 years accounted for 12,3% (25 enterprises) (Table 2). Table 2: Age and business form of the survey sample Number of Average Standard Minimum Maximum Variable observations value deviation value value Age of enterprise 206 10,65534 7,219394 1 57 15 years 25 Capacity (tons / year) 206 7.172,35 177.589,90 1 200.000 (Source: Author's synthesis) * Test the reliability of the scale The author evaluates the reliability of the scale according to each group of analysis indicators, including: (1) Group of indicators to analyze the efficiency of input supply activities; (2) Group of indicators to analyze the efficiency of production and business activities; (3) Group of indicators to analyze the efficiency of consumption activities; (4) Group of indicators to analyze the efficiency of overall operations. + Testing in groups (1): After performing group tests (1), The cronbach’s Alpha coefficient of the scale in the group of indicators to analyze the efficiency of input supply activities is 0.895> 0.6, ensuring reliability. However, indicators with the correlation coefficient of total variables 0.3. Thus, the results of reliability testing of scales in group (1) show that scales have an internally consistent group's reliability (Table 3). 221
8. Table 3: Results of testing the reliability of the scale of the indicators’ group (1) - 2nd Reliability Statistics Cronbach's Alpha N of Items .943 10 Item-Total Statistics Scale Mean if Scale Variance Corrected Item- Cronbach's Alpha Item Deleted if Item Deleted Total Correlation if Item Deleted CTDV01 32.02 76.541 .752 .938 CTDV03 31.99 76.751 .749 .938 CTDV04 31.91 76.178 .765 .937 CTDV05 31.73 77.096 .729 .939 CTDV06 31.92 74.720 .808 .935 CTDV07 31.87 76.817 .796 .936 CTDV08 31.86 75.396 .829 .934 CTDV09 32.11 78.051 .590 .946 CTDV10 31.84 76.038 .806 .935 CTDV11 31.89 74.076 .846 .933 + Testing in groups (2): The results in the first test showed that in this group Cronbach’s Alpha = 0.917 showed good measurement scale. In Table 4, the scales in group (2) are closely correlated. Table 4: Results of testing the reliability of the scale of the indicators’ group (2) – 1st Reliability Statistics Cronbach's Alpha N of Items .917 6 Item-Total Statistics Scale Mean if Scale Variance Corrected Item- Cronbach's Alpha Item Deleted if Item Deleted Total Correlation if Item Deleted CTSX13 17.27 28.441 .713 .909 CTSX14 16.93 27.765 .813 .895 CTSX15 16.93 29.000 .784 .900 CTSX16 17.41 28.584 .664 .916 CTSX17 17.12 27.190 .819 .894 CTSX18 17.23 27.028 .806 .895 222
9. + Testing in groups (3): Group (3) includes 05 criteria equivalent to 05 scales for analyzing consumption efficiency. The results show that Cronbach’s Alpha coefficient is 0.887, indicating the measurement scale is good. Correlation coefficients of all scales are> 0.3 and Cronbach's Alpha if Item Deleted Coefficient of all scales 0.6, which is highly reliable. To improve reliability and ensure maximum correlation between the analytical variables, the author removed the scale of CTKQ36 due to the total correlation coefficient of 0,013 <0.3. After that, the author checked the 2nd Cronbach’s Alpha coefficient for Group 4 and found that the Cronbach’s Alpha coefficient increased to 0.947 (Table 6), and the coefficients were satisfactory for factor analysis. Table 6: Results of testing the reliability of the scale of the indicators’ group (4) - 2nd 223
10. Reliability Statistics Cronbach's Alpha N of Items .947 14 Item-Total Statistics Scale Mean if Scale Variance Corrected Item- Cronbach's Alpha Item Deleted if Item Deleted Total Correlation if Item Deleted CTKQ24 43.07 71.365 .767 .942 CTKQ25 43.26 73.102 .686 .944 CTKQ26 43.20 73.939 .645 .945 CTKQ27 42.82 72.714 .668 .945 CTKQ28 43.03 71.521 .759 .943 CTKQ29 43.10 71.790 .748 .943 CTKQ30 43.13 71.890 .771 .942 CTKQ31 43.06 71.601 .807 .941 CTKQ32 43.10 73.097 .719 .944 CTKQ33 43.09 72.435 .732 .943 CTKQ34 43.08 71.988 .746 .943 CTKQ35 43.09 73.036 .727 .943 CTKQ37 43.04 71.930 .721 .944 CTKQ38 43.09 72.470 .701 .944 * Exploratory factors analysis (EFA) After testing Cronbach’s Alpha, the author removes 4 unsatisfactory scales. The set of scales included in the exploratory factor analysis consists of 35 scales. The results of the first EFA removed the CTDV09 scale because of the load factor at the same time in both groups. After the second EFA, all factors have a load factor greater than 0.5 and converge to the first four factor groups (Table 7). Table 7: Results of the EFA - 2nd KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .920 Approx. Chi-Square 5068.137 Bartlett's Test of Sphericity Df 561 Sig. .000 Rotated Component Matrixa 224
11. Component 1 2 3 4 CTKQ31 .814 CTKQ24 .810 CTKQ28 .788 CTKQ30 .782 CTKQ29 .777 CTKQ34 .765 CTKQ33 .756 CTKQ35 .749 CTKQ37 .748 CTKQ32 .725 CTKQ38 .722 CTKQ25 .700 CTKQ27 .700 CTKQ26 .685 CTDV11 .869 CTDV08 .862 CTDV10 .841 CTDV06 .832 CTDV07 .830 CTDV01 .800 CTDV03 .792 CTDV04 .779 CTDV05 .750 CTSX18 .877 CTSX17 .864 CTSX14 .863 CTSX15 .809 CTSX13 .786 CTSX16 .750 CTDR23 .878 CTDR19 .838 CTDR20 .827 CTDR21 .781 CTDR22 .751 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. (Source: Author’s analysis) 225
12. * ANOVA analysis of differences between enterprise’s groups In the qualitative research process, the author found a difference between manufacturing enterprises and commercial enterprises on the interest in 4 groups of analytical indicators. Therefore, after analyzing the factors, the researcher continues to analyze the differences between enterprises of different sizes. The analysis results in Table 8 show that, in indicators’ group 1, indicators’ group 2, and indicators’ group 3 there are no difference. For the indicators’ group 4, it has not been concluded because the variance is not uniform. Table 8: Results of analysis of differences in indicators in 4 groups between large scale enterprises and Small and medium enterprises Test of Homogeneity of Variances Levene Statistic df1 df2 Sig. CTDV 1.928 1 204 .166 CTSX 1.442 1 204 .231 CTDR .440 1 204 .508 CTKQ 5.110 1 204 .025 ANOVA Sum of Mean df F Sig. Squares Square Between Groups .230 1 .230 .238 .626 CTDV Within Groups 197.306 204 .967 Total 197.536 205 Between Groups 3.974 1 3.974 3.654 .057 CTSX Within Groups 221.866 204 1.088 Total 225.840 205 Between Groups 1.398 1 1.398 3.308 .070 CTDR Within Groups 86.218 204 .423 Total 87.616 205 Between Groups .027 1 .027 .064 .800 CTKQ Within Groups 87.377 204 .428 Total 87.405 205 Besides considering the difference in type of business production, the author continue to analyze whether there are differences in the indicators between 226
13. enterprises in large scale and enterprises in small and medium scale or not. Testing has shown that there is no difference between these two groups of enterprises in terms of usage indicator. 4. Discussion and Conclusion On the basis of understanding the nature of operational efficiency in enterprises is a process of causal connection, the author has developed a system of 33 indicators of business performance analysis of Vietnam’s paper enterprises including 4 groups: Group of indicators to analyze the efficiency of input supply activities; Group of indicators to analyze the efficiency of production and business activities; Group of indicators to analyze the efficiency of consumption activities and indicators’ group analyzing the efficiency of overall operations. From the research results, the author proposes some recommendations for Vietnam’s Paper Enterprises as follows: Firstly, it is recommended to use indicators to analyze the performance and needed resources for analysis. Analytical department should closely organize from the stage of collecting data to serve analysis. The source of the data can be based on financial statements and management reports, depending on the nature of the indicator. Determining the exact source of data for analysis right from the organization of accounting activities in the enterprise is necessary, this will help save costs by gathering information at the same time for related reporting and analyzing objectives. Secondly, need to analyze the business performance efficiency of enterprises annually. Paper enterprises should apply a system of indicators to analyze the business performance that has been surveyed and select from businesses in the same field. Enterprises are aware of the significance of analytical performance, but maintain regular analysis requires an understanding of the management department and the department participated in the analysis. From this study, the author recommends that enterprises should organize an analysis of each department and the overall analysis. Information data after analysis needs to be evaluated, compared between periods, find out the causes of the departments which operating ineffectively. There should be clear reward and punishment policies for departments to promote the effectiveness of each department and create general efficiency. Thirdly perform comparisons of the level of efficiency with other enterprises to determine the efficiency of own enterprises. Information transparency is one of the prerequisites for conducting business performance analysis. The higher the quality of the information used in the analysis, the more significant the indicators are in 227
14. controlling risks, will help attract investors, improve the ability of enterprises to access capital. Fourthly, enhancing social responsibility of enterprises through practical action as green production, saving and contributing to environmental improvement costs, contribute positively to the state budget, guiding consumers to classify waste paper correctly, training professional staffs. These activities are not only effective but also enhance the public image of enterprise. 5. References 1. Beaver, W. H. (1966). "Financial ratios as predictors of failure." Journal of accounting research: 71-111. 2. Brown, M. G. (1996). Keeping score: Using the right metrics to drive world- class performance. New York, Productivity Press. 3. Chen, K. H. and T. A. Shimerda (1981). "An empirical analysis of useful financial ratios." Financial Management: 51-60. 4. George E. Pinches, et al. (1973). "The stability of financial patterns in industrial organizations." The Journal of Finance 28: 389-396. 5. Hair, J., et al. (1998). "Multivariate data analysis 5 edition Prentice Hall." Upper Saddle River. 6. Ittner, C. D. and D. F. Larcker (2003). "Coming up short on nonfinancial performance measurement." Harvard business review 81(11): 88-95. 7. Kaplan, R. S., & Norton, D. P (1996). The balanced scorecard: translating strategy into action, Harvard Business Press. 8. Kaplan, R. S. N., David P (2001). Transforming the balanced scorecard from performance measurement to strategic management: Part I. Sarasota, American Accounting Association. 9. Nunnally, J. and I. Bernstein (1978). "Psychometric Theory McGraw-Hill New York Google Scholar." 10. Porter, M. E. (1985). Creating and Sustaining Superior Performance. 228