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
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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
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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
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