Factors affecting the use the operational efficiency measurement of Vietnamese manufacturing enterprises

Accounting staff's understanding and support of the highest

management authority for OE measurement, competition, corporate

governance decentralization, and tight corporate structure have a significant

positive effect on the use the financial measures of the Vietnamese

manufacturing enterprises.

- Competitive pressure, tight corporate structure and accounting staff’s

understanding and the highest governor's support for OE measurement have a

positive and positive impact on the using level the metrics customer aspect of

Vietnamese manufacturing enterprises

- Decentralization of corporate governance, tight corporate structure,

flexible corporate structure, and accounting staff’s understanding and the

highest support of the top management in the OE measurement has a positive

effect and same dimension to the extent to which the employee aspect metrics

are used.

- Competitive pressure in the market, decentralization in corporate

governance; tight corporate structure and flexible corporate structure have a

positive and positive impact on the use of internal process aspect metrics of

Vietnamese manufacturing enterprises

pdf13 trang | Chia sẻ: honganh20 | Ngày: 10/03/2022 | Lượt xem: 259 | Lượt tải: 0download
Bạn đang xem nội dung tài liệu Factors affecting the use the operational efficiency measurement of Vietnamese manufacturing enterprises, để tải tài liệu về máy bạn click vào nút DOWNLOAD ở trên
nce Scorecard model of Kaplan and Norton (1992) The common feature of these models is that there is a combination of financial indicators with non-financial indicators and strategy. Outstanding among the above models is the Balance Scorecard model which evaluates performance under various aspects of Kaplan and Norton (Bourne, 2003). Balance Scorecard is out of traditional financial spending, using a balance of financial and non-financial indicators to assess the reasons for the success of the strategy. Since its introduction up to now, the Balanced scorecard has been received and applied by many businesses, and has brought success to businesses. 2.2. Overview of research on the influence of factors on OE measures in enterprises. 2.2.1. Studies on the use of OE measures Although there are not many studies on the level of using OE measures, the studies related to the level of use and the importance of the measures of operational efficiency as a component of the management accounting are quite popular. The study of Chenhall and Langfield-Smith (1998), developed from the research model of De Meyer (1989) and Miller (1992). In this study, the OE measurement system is one of the 5 components of the management accounting system: product costing, planning, decision suppor,performance evaluation measurement and strategy support. The study shows the application level as well as the benefits obtained from the application of OE measures of large-scale in Australian enterprises, but Chenhall and Langfield-Smith (1998) do not show which factors have affects the level of application of operational efficiency measures as well as the degree of 6 influence of factors on the degree of application of measures of operational efficiency in enterprises. There are also studies on the use of performance measures by authors: Abdel-Kader and Luther (2006; 2008), Ahmad and Mohamed Zabri (2012), Ahmad and partners (2015). , Pierce and O'Dea (1998), Hoque (2004), Kennerley and Neely (2002), Abdel-Maksoud and partners. (2005; 2008), Tymon and partners. (1998), Speckbacher (2003), Abernethy and partners (2004), Abernethy &Bouwens (2005), Ismail (2007), Tran Quoc Viet (2013), Vu Thi Sen (2018). Xiao and partners (2006), Nishimura (2003), Sulaiman and partners (2004), Hyvonen (2005), Abdel- Maksoud and Abdel-Kader (2005; 2007), Gosselin (2005), Gomes and partners. ( 2011), Bhimani and Langfield-Smith (2007), Abdel-Maksoud and Abdel-Kader (2007). 2.2.2. The researching works effectedby factors using of OE measures One of the typical studies related to the effected factors using operational efficiency measures is that of Zaman and partners (2016). The major contribution of this study is to synthesize the research related to the influence of factors on the use of OE measures. In addition, studies suggest factors affecting the use of operational efficiency measures such as the research of the authors:Amat and partners (1994), Halma and Laats (2002), Sulaiman (2003). , Anderson and Larnen (1999), Wu, Boateng and Drury (2007), Abdel-Kader and Luther (2008), Subasinghe and AT Fonseka (2010), Abdel and partners. (2011), Ahmad Amah (2012), Lee, C, L. & Yang, HJ (2011), Doan Ngoc Phi Anh (2012), Chen and aprtners (2014), Sulaiman and partners (2015), Blau (1970), Chenhall and Langfield-Smith (1998), Pierce and O'Dea (1998), Mohamed Basheikh and Abdel-Maksoud (2005), Lillis and van Veen-Dirks (2008), Tran Ngoc Hung (2016), Thai Anh Tuan (2019). 2.2.3. Conclusions fromworks Firstly, up to now, there have been many studies to find the causes and explain differences in the use of management accounting tools. However, these studies are mostly done in developed countries. In developing countries 7 such as Malaysia, Thailand, Banglades, Jordani, Sri Lanca, etc., there are also many studies on the situation of the application of management accounting methods and factors influencing the use of management accounting tool has been implemented. In Vietnam, up to now there has not been any research on the use of OE metrics and the effects of the factors on the use of OE metrics in Vietnamese enterprises. Second, the studies on the relationship between the factors with the use of OE measures in the world are very limited and are often part of the study of factors affecting the management accounting application. Thirdly, although it has shown the influence of internal and external factors on the change of management accounting techniques and the use of management accounting in enterprises, these studies do not mention much about the effect of factors to the change and the use of operational efficiency measures. Fourth, in Vietnam, although there have been 2 studies on the effects of factors on the management accounting application by Tran Ngoc Hung and Thai Anh Tuan, there are no studies on the effects of factors using the OE measures in Vietnamese enterprises. Therefore, this is a space for the thesis to study the relationship of factors to the use of the OE measures in Vietnamese enterprises. 2.3. The theory studies on the influent factors on the use of OE measures in enterprises 2.3.1. Random theory Each business has its own characteristics in terms of operating environment, business goals, cultural organization, and operational strategy, etc. Therefore, in order to match the objectives, culture and successful factors, each enterprise needs its own management accounting system as well as its own OE measurement system suitable for the business’s characteristics. Therefore, the author uses the random theory as the foundation for his research 8 2.3.2. Innovative diffusion theory The theory of innovative diffusion is one of the oldest social science theories. This theory explains how an idea or product acquires power diffuses or is accepted by a particular community or social system over time. 2.3.3. Stakeholders theory Business activities not only affect owners and employees, but also affect and be associated with the interests of many objects. Stakeholder theory serves as a basis for explaining the use / non-use of a firm's OE measure. This theory is also the basis for explaining top-management support for OE measurement as an independent variable into the research model. CHAPTER 3 THEORY BUILDING AND METHODOLOGY 3.1. Research design According to Hair and partners (2007), research design provides the most relevant information to solve research questions or hypotheses. To answer research questions and hypotheses, three separate research designs are required: explorative studies; descriptive studies; and causalities studies (Hair and partners, 2014). Explorative studies uses qualitative methods to discover the factors that affect the using level the OE measures in enterprises. Descriptive studies is used to answer questions about the current status of using OE measures in enterprises. In order to answer the question about the effects of factors on the use of operational efficiency measures in enterprises, descriptive data is also collected for analysis and research on causal relationships between factors in the model with the using level the operational efficiency measures. 3.1.1. Qualitative research Qualitative research is done through in-depth interviews with experts to select evaluation criteria and factors affecting the using degree evaluation criteria in the research model. 9 Summary of discussion results with experts on selected independent variables in the model is as follows: Table 3.1. Summary of discussion results on independent variable selection Expected models Results with experts Independent variable Original research Business size Piercer & O’Dea (1998), Williams and Seaman (2001), Xiao (2006), Abdel-Kader and Luther (2008), Ahmad (2012), Halbouni (2014), Al-Omiri and Drury (2007), Karanja (2013), etc Accept Competitive pressure Bruns and Kaplan (1991), Wijewardena, H. and De Zoysa, A. (1999), Luther and Longden (2001), Chenhall (2003), Doan Ngoc Phi Anh (2012), Ahmad (2012) Accept Decentralization level Doan Ngoc Phi Anh (2012), Ahmad (2012) Adjust to decentralization Business structure Grover (1993), Lee & Yang (2011) Accept Activity time Doan Ngoc Phi Anh (2012), Karanja (2013) Reject Join of highest governor in OE measurement Premkumar, (1995), Brown (2004), Ahmad (2012) Adjust to highest support of governor to OE measurement Professional Halma andLaats (2002); Al-Omiri Change to staff 10 Expected models Results with experts Independent variable Original research qualification of accounting staff (2003) Ismail and King (2007), Allahyari andRamazani (2011), Ahmad (2012), Doan Ngoc Phi Anh (2102), Halbouni (2014) knowledge about OE measurement 3.1.2. Building research hypotheses Enterprise size can have an important influence on the way of organizing and using OE metrics. Hypothesis H1-1. Company size has a positive influence on the use of OE metrics. Competition in the market forces businesses to pay attention to OE to maintain a competitive advantage with competitors Hypothesis H1-2: Competitive pressure has a positive influence on the level of using the operational efficiency measures Decentralization of decision making raises the need for information to make decisions and evaluate OE. The relationship between decentralization and the use of operational efficiency measures has been previously studied by some scholars and the research results are also very different. Hypothesis H1-3: The decentralization in enterprises has a positive influence on using degree the operational efficiency measures.. The studies of Abernethy and partners, (2004); Langfield-Smith (1997); Luft and Shields (2003) showed a close relationship between firm structure and the level of using OE measures. Hypothesis H1-4. Different business structures have different effects on using level the OE metrics. 11 The highest understanding of the operational efficiency measurement can be a factor affecting using level of the measures of the operational efficiency. The governors need information to evaluate, reward and make decisions, rise to the need to use OE metrics to meet. Hypothesis H1-5. The highest support of governor has a positive effect on using level of the OE measures. The accountant's understanding of OE measurement can be an important factor that facilitates the use of OE metrics. The accountants are well trained, have a full understanding of OE measurement, understanding the role and impact of each metric on the behavior of managers and the success of the business. Hypothesis H1-6. The accountant's understanding of OE measurement has a positive influence on the level of using the OE metrics. 3.1.3. Research model Applying the random theory, theory of innovation diffusion, stakeholder theory, the thesis proposes a research model about influent factors on using level of the measures of operational efficiency in the Vietnamese enterprises as follows: Developed from Ahmad, 2012, Doan, 2012 Conpetition pressure Decentralization Business structure Governor’s supporting Accounting staff's understanding Scale Using level the operational efficiency measure H1 + H2 H3 H4 + H5 H6 + + + + + 12 In this research model, the dependent variable is the using degree of the OE measures in enterprises. The independent variable in this model is the factors that can affect the using level OE measures in enterprises. The independent variables include: • Competitive pressure • Decentralization • Business structure • The highest rating of governor for the OE measurement • The accounting staff's understanding of OE measurement • Size of enterprise (control variable) The equation reflecting the relationship between the independent variables and the expected dependent variable is as follows: Yi = β0 + β1X1 + β2X2 + ... βnXn + ɛ In which: Y: The using level of operational efficiency measures β0: Constant βi: Influence rate of the independent variable i on the dependent variable i. Xi: Influence of the independent variable i on the dependent variable i. ɛ: Unstudied effective factors 3.2. Sampling method 3.2.1. Sample object and data collection method Sampling object is Vietnamese manufacturing enterprises. Due to limited time and resources, the enterprises were selected according to the convenient sampling method, mainly in Hanoi and the Northern provinces, around Hanoi. Surveys are used to collect data for the description and testing of hypotheses. The questionnaires were sent directly to the company, sent by post or surveyed online through the website at https://docs.google.com/forms. 13 To facilitate data collection and processing, the answered paper questionnaires after being answered are also entered into the form on the application at https://docs.google.com/forms 3.2.2. Sample size The thesis aims to collect from 140-160 surveys. The sample of the survey will include businesses of different sizes, organizational forms and ownership composition. To collect the required number of samples for the study, the author uses convenient sampling methods. With about 450 submissions, the author hopes to receive from 150 to 200 responses 3.3. Research order The study will be done in the following steps: Step 1 Material study Step 2 Independent variable determination and survey building Step 3 Trail-test survey Step 4 Adjust survey, carry out survey Step 5 Clarify material Step 6 Material analyst with SPSS 20 and SmartPLS 3 software CHAPTER 4 RESULTS OF THE EFFECTIVE FACTORS ON USE OE MEASURES IN THE VIETNAMESE MANUFACTURING ENTERPRISES 4.1. Descriptive statistics of research samples Number of questionnaires sent out and sent by post, email (link and soft copy of survey), through surveyors to the enterprise to meet the chief accountant, department head or accountant to interview and fill in the questionnaire was close to 450 votes. The number of votes collected was 171, the number of votes that could be used after clarifying was 153. The response rate was nearly 38.0%. The percentage of usable votes to the total number of votes collected is 89.4%. 14 4.2. Results of the survey on the situation and the using level of OE measures in Vietnamese manufacturing enterprises Using frequency analysis function of SPSS20 software to perform statistics to describe the current situation of applying OA measures in Vietnam's manufacturing enterprises. The results show that manufacturing firms pay more attention to productivity, production time, revenue growth, and profit but less attention to the number of returned products, number of failures machine, quitting rates and information related to occupational accidents 4.3. Study the effects of independent variables on the using level of OE measures in Vietnamese manufacturing firms. Checking the model's criteria shows that all models have internal uniformity reliability, convergence value and the necessary differentiating value to evaluate the effects of independent variables on the dependent variable. UsingBoostrap for each model using SmartPSL 3 software gave the following results: Model 1 This model assesses the effect of random variables on the use of financial measures including Revenue growth rate; Cash flow; Profit growth rate; Actual profit / cost estimate; Return on investment (ROI); Return on assets (ROA) and Return on equity (ROE). Table 4.20. Beta and P-valuecoefficients of model 1 Hypothesis Relationship Beta P Values Results H1-1 Scale ->Finance -0,013 0,827 Reject H1-2 Competition -> Finance 0,146 0,046 Accept H1-3 Decentralization -> Finance 0,272 0,010 Accept H1-4 Tidiness -> Finance 0,076 0,356 Reject 15 H1-5 Flexibility -> Finance 0,256 0,009 Accept H1-6 HB & UH -> Finance 0,405 0,000 Accept PLS-SEM theoretical model on the influence of independent variables on the use of financial measures in Vietnamese manufacturing enterprises F1 = 0.405X6 + 0.272X3 + 0.226X5 + 0.146X2 In which: F1: Usage of financial metrics X2: Competition X3: Decentralization X5: Flexible structure X6: Understanding and support Model 2 Model 2 tests hypotheses about the relationship between the independent variables and the use of customer aspect measures including: Customer satisfaction; Number of customer complaints; On-time delivery rate; Number of new customers and Rate of revenue from new customers Table 4.21. Beta and P-value coefficientsof model 2 Hypothesis Relationship Beta P Values Results H1-7 Scale -> Customers -0,157 0,116 Reject H1-8 Competition ->Customers 0,263 0,001 Accept H1-9 Decentralization-> Customers 0,138 0,138 Reject H1-10 Tidiness -> Customers 0,192 0,023 Accept H1-11 Flexibility -> Customers 0,176 0,069 Reject H1-12 HB & UH -> Customers 0,418 0,000 Reject Source: Authors' analysis using SmartPLS 3 software 16 PLS-SEM theoretical model is about the influence of independent variables using customer aspect metrics in the Vietnamese manufacturing enterprises is: F2 = 0.418X6 + 0.263X2 + 0.192X4 In which: F2: Using level of customer aspect metrics X2: Competition X4: Tight structure X6: Understanding and support Model 3 Model 3 tests hypotheses about the relationship between the independent variables and the using level of employee dimensions, including: Rate of employees quitting; Employee Training Costs and Staff Satisfaction Table 4.22. Beta and P-value coefficients of model 3 Hypothesis Relationship Beta P Values Results H1-13 Scale -> Staff -0,021 0,742 Reject H1-14 Competition -> Staff 0,123 0,190 Reject H1-15 Decentralization ->Staff 0,178 0,019 Accept H1-16 Tidiness ->Staff 0,254 0,003 Accept H1-17 Flexibility ->Staff 0,215 0,024 Accept H1-18 HB &UH ->Staff 0,332 0,004 Accept Source: Authors' analysis using SmartPLS 3 software The PLS-SEM theoretical model of the tight corporate structure influence on the using level of employee dimensions in the Vietnamese manufacturing enterprises is: F3 = 0.332X6 + 0.254X4 + 0.215X5 + 0.178X3 In which: 17 F3: Using level of employee aspect metrics X3: Decentralization X4: Tight structure X5: Flexible structure X6: Understanding and support Model 4 This model tests hypotheses about the relationship between the independent variables with the using level of internal process aspect measures, including: Number of accidents; Amount of compensation and treatment for the accident; Scrap rate; Labor productivity; Production time; Time off work and Number of hours / number of failures. Table 4.23. Beta and P-value coefficients of model 4 Hypothesis Relationship Beta P Values Results H1-19 Scale -> Internal -0,024 0,670 Reject H1-20 Competition ->Internal 0,246 0,020 Accept H1-21 Decentralization - >Internal 0,244 0,017 Accept H1-22 Tidiness ->Internal 0,228 0,007 Accept H1-23 Flexibility ->Internal 0,221 0,033 Accept H1-24 HB & UH ->Internal 0,164 0,241 Reject Source: Authors' analysis using SmartPLS 3 software PLS-SEM theoretical model on the effects of independent variables on the use of internal measures in the manufacturing enterprises: F4 = 0.246X2 + 0.244X3 + 0.228X4 + 0.221X5 In which: F4: Using level of internal metrics X2: Competition 18 X3: Decentralization X4: Tight structure X5: Flexible structure Model 5 Model 5 tests hypotheses about the relationship of the effects of independent variables on the use of product quality measures such as: Percentage of defective products; The rate of products returned; Quality cost and Repair and warranty cost. Table 4.24. Beta and P-value coefficients of model 5 Hypothesis Relationship Beta P Values Results H1-25 Scale ->Quality product -0,012 0,875 Reject H1-26 Competition ->Quality product 0,260 0,002 Accept H1-27 Decentralization ->Quality product 0,226 0,006 Accept H1-28 Tidiness ->Quality product 0,224 0,004 Accept H1-29 Flexibility ->Quality product 0,228 0,007 Accept H1-30 HB & UH ->Quality product 0,264 0,000 Accept Source: Authors' analysis using SmartPLS software 3 F5 = 0.260X2 + 0.226X3 + 0.224X4 + 0.228X5 + 0.264X6 In which: F5: Using level of quality metrics X2: Competition X3: Decentralization X4: Tight structure X5: Flexible structure X6: Understanding and support Model 6 19 Model 6 tests hypotheses about the relationship between the independent variables and the use of renovation product measures. The metrics chosen to represent product renovation are: Number of new products to the market; Time new product to market and Percentage of sales from new products. Table 4.25. Beta and P-value coefficients of model 6 Hypothesis Relationship Beta P Values Results H1-31 Scale ->Renovation product 0,037 0,554 Reject H1-32 Competition->Renovation product 0,164 0,028 Accept H1-33 Decentralization ->Renovation product 0,134 0,205 Reject H1-34 Tidiness ->Renovation product 0,233 0,007 Accept H1-35 Flexibility ->Renovation product 0,218 0,031 Accept H1-36 HB & UH ->Renovation product 0,353 0,001 Accept CHAPTER 5 DISCUSSIONS, RECOMMENDATIONS AND CONCLUSION 5.1. Research issues and conclusions To answer the question "The effect of some factors on using level the OE measures in the Vietnamese manufacturing enterprises", the thesis has specified 7 initial hypotheses into 36 hypotheses reflecting the relationship between factors and groups of operational efficiency measures. Based on the results of PLS-SEM analysis to test hypotheses reflecting the relationship between the dependent variables and the independent variables, 11 assertive hypotheses can be rejected. From 25 confirmed 20 hypotheses are accepted and the results of PLS-SEM model analysis allow the following conclusions to be made: - Accounting staff's understanding and support of the highest management authority for OE measurement, competition, corporate governance decentralization, and tight corporate structure have a significant positive effect on the use the financial measures of the Vietnamese manufacturing enterprises. - Competitive pressure, tight corporate structure and accounting staff’s understanding and the highest governor's support for OE measurement have a positive and positive impact on the using level the metrics customer aspect of Vietnamese manufacturing enterprises - Decentralization of corporate governance, tight corporate structure, flexible corporate structure, and accounting staff’s understanding and the highest support of the top management in the OE measurement has a positive effect and same dimension to the extent to which the employee aspect metrics are used. - Competitive pressure in the market, decentralization in corporate governance; tight corporate structure and flexible corporate structure have a positive and positive impact on the use of internal process aspect metrics of Vietnamese manufacturing enterprises - Competitive pressure in the market; decentralization of corporate governance, strict corporate structure; the flexible corporate structure and accounting staff’s understanding and the highest governor's support for OE measurement have a positive and positive impact on the degree of use of product quality metrics of Vietnamese manufacturing enterprises - Competitive pressure in the market, tight corporate structure, flexible corporate structure and accountant's understanding and the highest support of the governor to OE measure has a positive effect and same direction to the extent of using the measures of product innovation by Vietnamese manufacturing enterprises. 21 5.2. Implications and meanings of research From the above analysis results, the implications, meanings and recommendations are drawn as follows: - The manufacturing enerprises need to be aware of the increasing pressure of competition in the market and the role of the OE measurement system in providing information for decision-making, affecting the batter's behavior to proactively stay ahead of building a effective measurement system that match goals and business strategies to provide indicators for the position and performance of departments in the enterprise to improve business efficiency, deal with

Các file đính kèm theo tài liệu này:

  • pdffactors_affecting_the_use_the_operational_efficiency_measure.pdf
Tài liệu liên quan