1 

 

INTRODUCTION 

Unfortunately, the fate of the textile industry in Indonesia due to the impact of the Corona 
pandemic resulted in job cuts of at least 2.1 million over the past year. (Kartiwa, n.d.). Though this 
industry is beneficial to the Indonesian economy because this industry can employ 3.73 million 
Indonesians and also become the land of state income from exports. Not only external factors, but 
the decline in the performance of the textile industry is also due to internal factors. Managers' 
inability to deal with environmental uncertainty is the cause of declining productivity. (Pedroso, 
Gomes, & Yasin, 2020), In addition, the inability to integrate units in the organization is the cause 
of the management accounting system not running and its impact on the output of inaccurate 
information. (Gericke, Klesse, Winter, & Wortmann, 2010).  

Some studies that examine management accounting systems, such as findings (Giannetti, 
Cinquini, Miolo Vitali, & Mitchell, 2021), That the management accounting system can change due 
to the results of the process. Management accounting systems can directly affect a manager's 
performance. (Pedroso et al., 2020). (Garasyim, Bondarenko, Klym, Karpenko, & Bondarchuk, 

 INABILITY TO ADAPT TO ENVIRONMENTAL CHANGES CAUSES 
THE DECLINING PERFORMANCE OF INDONESIA'S TEXTILE 
INDUSTRY 

Volume: 4 

Number: 1 

Page: 1-9 

1Rima RACHMAWATI, 2Evi OCTAVIA 
1,2Faculty of Economics and Business, Widyatama University, Indonesia 

Corresponding author: Rima RACHMAWATI  

Email: rima.rachmawati@widyatama.ac.id 

Article History: 

Received: 2022-10-25 

Revised: 2022-12-11 

Accepted: 2023-01-15 

 

Abstract: 

The ability of managers in the face of environmental uncertainty is the main key 
to achieving competitive advantage. The decline in the performance of the 
Indonesian textile industry is due to the low quality of management accounting. 
This quantitative research aims to prove that the ability to deal with 
environmental uncertainties affects the quality of management accounting as 
well as its impact on the quality of information. The method used in this research 
is Explanatory verification research to find out what and how far the factors that 
affect the quality of management accounting information. This study involved 
textile companies registered with the Indonesian Textile Association, a total 
population of 85 companies with sampling methods using power analysis at a 
significance level of 5% with statistical power. Data analysis using Structural 
Equation Modeling-Partial Least Square includes measurement and structural 
models. The results of this study prove that the variability of management 
accounting information systems is built by the variability of environmental 
uncertainties. While the variability in the quality of management accounting 
information is formed by the variability of management accounting systems. 
Following up on the findings of this study, the ability to deal with environmental 
uncertainties is the main key to optimizing management accounting systems in 
generating management accounting information. 

Keywords: Environmental Uncertainty; Management Accounting Systems; 
Information Quality; Industry Textile. 

 

 

 

 

Cite this as: RACHMAWATI, R1., OCTAVIA, E2. (2022) “Inability to Adapt to 
Environmental Changes Causes the Declining Performance of Indonesia's 
Textile Industry.” International Journal of Environmental, Sustainability, and 
Social Sciences, 4 (1), 1-9. 

mailto:rima.rachmawati@widyatama.ac.id


 

2 

2020), An essential component of management accounting reporting is reliable and timely 
spending. Some of these researchers explain management accounting systems in their output 
aspects while this study views management accounting systems in their characteristic aspects. The 
purpose of assessing the characteristics of the management accounting system in this study wants 
to know what kind of characteristics are needed by the industry to maintain its competitiveness.  

The function of management is to make decisions, which are based on scientific studies, not 
instinct alone, this scientific study is in the form of information so that the information is of quality, 
which means it is worth using as a basis for decision making. Quality information is born from 
quality information systems, namely, integration, accessibility, formalization, and enrichment of 
media (Heidmann, Schäffer, & Strahringer, 2008). The results of this study have this goal to 
evaluate/determine/provide recommendations, especially in the textile industry that the quality 
of management accounting systems must be maintained to create quality information, namely 
scope, timeliness, accuracy, format and relevancy. (Heidmann et al., 2008).  

This research wants to prove that the concept of a quality management accounting system 
will produce quality information. The information will be used by management to make decisions 
so that environmental uncertainties can be faced. The impact of this research is not only developing 
science but also can solve problems in the textile industry, especially in Indonesia. This research 
results in a quality development model of management accounting systems. Researchers 
recommend developing management accounting system models with variable influences other 
than the environment, such as information technology, organizational structure, and others. 

 

METHODS 

Research objects use environmental uncertainties, management accounting systems, and 
quality management accounting information. Explanatory verification research is to determine 
what and how far the factors affect the quality of management accounting information. Data is 
collected between times. Operationalization of research variables as follows; Variable independent 
is the level of change and complexity of the corporate environment that can influence managers to 
predict the likelihood of future events thus affecting the activities of management accounting 
systems. A management accounting system (variable Y) is a subsystem device that will process 
data with characteristics of integration, flexibility, accessibility, formalization, and enrichment of 
media. Quality management accounting information (variable Z) is the output of a management 
accounting system that managers use to perform their functions with scope characteristics, timely, 
accuracy, format and relevance.  

This research analysis unit is a textile company registered with the Indonesian Textile 
Association with observations on accounting units at the middle manager level. Textile company 
research population (API version) with simple random sampling with minimum sample size using 
the concept of power analysis with a significance of 5% as much as 85 samples sample (Hair, Hult, 
Ringle, & Sarstedt, 2021). Data analysis using Structural Equation Modeling-Partial Least Square 
includes measurement and structural models. 

 

RESULTS AND DISCUSSION 

Questionnaire data filled out by 85 respondents was taken from textile companies registered 
with the Indonesian Textile Association (API) in 2014; the data was processed with smart PLS 3.0 
application with structural equation modeling-partial least square (PLS-SEM) analysis technique, 
namely data processed and calculated with levels, (1) evaluation of outer models and (2) evaluation 



 

3 

of inner models. Evaluation of outer models by measuring the validity and reliability of the model 
for which the evaluation results have qualified. 

Evaluation of the inner model (structural model) among others; R-square values, bootstrapping 
results, hypothesis test results. 

a. R-square value 

The R-Square value is used to assess how much influence exogenous latent variable values 
have on endogenous variables. Based on the data output results using SmartPLS 3.0 Professional 
software, the R-Square value is generated as follows. 

 

Tabel 1. R-Square 

  R-Square 

Quality Of Management Accounting Information (Y2) 0.539 

Quality of Management Accounting Information Systems (Y1) 0.345 

 

The results of this calculation measure the Quality Criteria of the dimensions of complexity 
levels and changes in exogenous variables, which can be stated that the quality of the criteria in 
indicators from the dimensions of exogenous variables can affect the indicators attached to the 
dimensions of integration, flexibility, accessibility, formalization, and media richness by 34,5%. In 
the scope dimension, the timeliness, accuracy, formatting, and relevancy of endogenous variables 
can be affected by variable X with indicators attached to the dimensions of complexity and change 
levels. The effect of X on Y2 is worth 0.539 or can be rounded to 0.54 (54%).  

Next, the R-Square value for endogenous variables is done as an assessment of goodness of 
fit that can be known through the value of Q2. The value of Q2 has the same meaning as the co-
efficient determination (R-Square) in the regression analysis. The model is said to be getting fit 
with data if the goodness of fit value is good. To measure the value of the fit, an estimated Q2 value 
can be calculated as follows (Hair, Hult, Ringle, & Sarstedt, 2021): 

Q2 = 1- (1-R12) (1-R22) 
Q2 = 1- (1-0,345) x (1-0,54) 
Q2 = 1- (0,655 x 0,46) 
 Q2= 1- 0,3031 
     = 0,6969 
     = 0,70   

Based on the estimate results, it has been known that the value of Q2 of 0.6969 rounded to 
0.70 (70%) or with other interpretations that the amount of diversity of research data can be 
explained by the structural model processed. Through these results, the structural model in the 
study was declared to have fulfilled an excellent good fit.  

b. Bootsrapping Result 

This calculation aims to test and minimize the problem of abnormal data from the results of 
the study. This expansion is done by observing the relationship between constructs or structural 
variable models. The test results can be seen as follows: 



 

4 

 
Figure 1. Bootsrapping 

 

From the design of the structural model (inner model), the early exogenous and endogenous 
latent variables had 26 manifest variables (indicators). After the recount twice, there were only 22 
variables left. Some of these variables; P1, P2, P3, P4, and P5 of variable X; P6, P7, P8, P9, P10, P11, 
P12, and P13 of variable Y1; as well as P16, P18, P19, P20, P21, P22, P23, P24, P25, and P26 of the 
Y2 variable which is then calculated by bootstrapping analysis such as the picture above. The 22 
variables assess that the indicator on the bootstrapping image of the Most Powerful Environmental 
Uncertainty (X) influence is the P1 of the complexity level dimension. P1 is able to influence several 
indicators of both endogenous variables (Y1 and Y2) of 25,596.  

While the most strongly influenced by Environmental Uncertainty (X) is the P7 indicator 
(format dimension) of the Management Accounting Information System Quality variable (Y1) with 
an influence value of 20,208. In other evaluations, the influence of the Environmental Uncertainty 
variable (X) on the Management Accounting Information Quality (Y2) variable, mainly on the P23 
indicator (integration dimension) has an effect of 19,637. In another description, it can be stated 
that the P1 of the most exogenous variables affects the indicators P17 and P23 with a relatively thin 
difference of influence, which is 0.959. 

c. Hypothesis Test Result 

T-Statistics Test Result. Test the significance value of the predictive model in structural 
model testing can be seen in the t-statistical values listed in the path coefficient table on the 
bootstrapping of smart PLS applications. The coherency of the path describes the magnitude of the 
evaluation value of the significance of the structural model that can be reviewed through the t-
statistic table of exogenous variables to endogenous variables as follows: 

 

Tabel 2. T-Statistic 

  Original 
Sample 

T-Statistics P Values 

Environmental uncertainty (X) → quality of management accounting 
information (Y2) 

-0.036 0.287 0.774 

Environmental uncertainty (X) → quality of management accounting 
information systems (Y1) 

0.587 7.996 0.000 

Management Accounting Information System Quality (Y1)-> Quality 
of Management Accounting Information (Y2) 

0.754 7.747 0.000 

 



 

5 

Before hypothesis testing was conducted, it was known that the T-table critical value for trust 
levels reached 95% (α by 5%) and the following degrees of freedom (df) was 83%. Based on the 
output results, the t-statistical value on H1 is declared insignificant with an evaluation value of 
0.287 or less than the standard value (1.96), this is also supported by the evidence of p values of 
0.774 or greater than the standard value (0.05) which means the direct effect X is not significant to 
Y2. The calculation statement above shows that environmental uncertainty has no significant effect 
on the quality of management accounting information. 

The discussion indirectly also proves that H1 based on the original sample value has a 
negative relationship with a minus evaluation value of -0.036. In the second part of the hypothesis 
(H2), the significance value in t-statistics shows good significance with a value of 7,996 and a p-
value of 0.000 and has a positive relationship based on the original sample value (0.587). 
Environmental uncertainty (X) has a positive and significant effect on the quality of management 
accounting information systems (Y1). 

In the third hypothesis (H3) itself, the quality of management accounting information system 
to the quality of management accounting information also has a positive and significant effect. The 
confirmation is described through a positive original sample value of 0.754, and a significant t-
statistics evaluation value of 7.747, as well as a p-value of 0.000 or, can be described through the 
following table: 

 

Table 3. Hypothesis 

Hypothesis Construct Decision 

1 
Environmental Uncertainty (X) has no positive and insignificant effect on 

the Quality of Management Accounting Information (Y2) 

Hypothesis 

Rejected 

2 
Environmental Uncertainty (X) has a positive and significant effect on the 

Quality of Management Accounting Information Systems (Y1) 

Accepted 

Hypothesis 

3 

Management Accounting Information System Quality (Y1) has a positive 

and significant effect on the Quality of Management Accounting 

Information (Y2) 

Accepted 

Hypothesis 

 

Specific Indirect Effects values on the Inner Model. The step of evaluating structural 
models can be done by evaluating or paying attention to the value of the significance of 
relationships between variable constructs. This can be viewed from the coefficient path in the inner 
model that describes the strength of relationships between variables. The direction in the path must 
correspond to the hypothesized theory, and its significance can be evaluated on the t-statistics 
present in the resampling output. Thus, the critical value can be seen in the table of specific indirect 
effects in the inner model: 

 

Tabel 4. Specific Indirect Effects Table 

  Original Sample T Statistics  P Values 

Environmental uncertainty (X) → quality of 
management accounting information 
system (Y1)-> quality of management 
accounting information (Y2) 

0.443 5.033 0.000 

 

The evaluation output in the specific indirect effect table indicates that the direction in path 
X to Y2 through Y1 is positive with the original sample value of 5,033 (<1.96). Also, the relationship 



 

6 

X to Y2 through variable Y1 is expressed significantly with a t-statistics value of 5.033 and p values 
of 0.000 (<0.05). Therefore, this statement illustrates that Environmental Uncertainty has a positive 
and significant relationship to the Quality of Management Accounting Information through 
quality intervening variables. 

 

CONCLUSIONS 

Based on the phenomenon and the results of the study concluded that the inability of 
management in the face of environmental uncertainties affects the quality of management 
accounting information systems. Furthermore, management accounting information systems affect 
the quality of management accounting information. The variability in the ability to deal with 
environmental uncertainties formed the quality variability of the management accounting system 
by 53.9%. The value indicates that if management accounting wants to be improved in quality, it 
must be able to improve its ability to deal with environmental uncertainty both the level of 
complexity of the environment and the level of change. The results of this study also concluded 
that the quality of management accounting information is influenced by the quality of management 
accounting systems. The variability of management accounting quality formed the variability of 
management accounting information quality by 34.5%. This means that quality management 
accounting information is also generated from quality management accounting information 
systems. The implication of the results of this study is that we become aware that the ability to deal 
with environmental changes is the main key to forming a quality management accounting system, 
therefore only from a quality management accounting system that management accounting 
information generated. Likewise, it is essential to realize that quality information will help 
management carry out its decision-making function. 

  

REFERENCE 

A. Hammad, S., Jusoh, R., & Ghozali, I. (2013). Decentralization, perceived environmental 
uncertainty, managerial performance and management accounting system information in 
Egyptian hospitals. International Journal of Accounting and Information Management, 21(4), 
314-330. https://doi.org/10.1108/IJAIM-02-2012-0005  

Agbejule, A., & Burrowes, A. (2007). Perceived environmental uncertainty, supply chain 
purchasing strategy, and use of MAS information. Managerial Auditing Journal, 22(9), 913-
927. https://doi.org/10.1108/02686900710829417  

Ah Lay, T., & Jusoh, R. (2017). Organizational Capabilities, Strategic Management Accounting and 
Firm Performance. Jurnal Akuntansi Dan Keuangan Indonesia, 14(2), 222-246.  
https://doi.org/10.21002/jaki.2017.12  

Chong, V. K., Chong, K. M., Chong, V. K., Chong, K. M., Huynh, Q. L., & Vinh, T. (2010). 
Management Accounting Systems, Perceived Environmental Uncertainty and Companies ' 
Performance in. International Journal of Academic Research, 2(1), 195-201. 

Drobyazko, S., Shapovalova, A., Bielova, O., Nazarenko, O., & Yunatskyi, M. (2019). Evaluation of 
effectiveness of responsibility centers in the management accounting system. Academy of 
Accounting and Financial Studies Journal, 23(6), 1-6. Retrieved from 
https://www.scopus.com/inward/record.uri?eid=2-s2.0 
85081907900&partnerID=40&md5=ffedcae11af8ef541726cdf8d835fea0  

https://doi.org/10.1108/IJAIM-02-2012-0005
https://doi.org/10.1108/02686900710829417
https://doi.org/10.21002/jaki.2017.12
https://www.scopus.com/inward/record.uri?eid=2-s2.0%2085081907900&partnerID=40&md5=ffedcae11af8ef541726cdf8d835fea0
https://www.scopus.com/inward/record.uri?eid=2-s2.0%2085081907900&partnerID=40&md5=ffedcae11af8ef541726cdf8d835fea0


 

7 

Efendi, D., & Kusuma, E. A. (2021). The Role of the Management Accounting System and Decision-
Making Style on Managerial performance. Jurnal Keuangan Dan Perbankan, 25(1), 144-161. 
https://doi.org/10.26905/jkdp.v25i1.5330  

Egorova, S., Bogdanovich, I., Kistaeva, N., & Iudanova, L. (2020). Management Accounting As a 
Tool For Organization Of Information On Innovations. Proceedings of the 2nd International 
Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020. 
https://doi.org/10.1145/3444465.3444467   

Fitriati, A., & Mulyani, S. (2015). Factors That Affect Accounting Information System Sucess and 
its Implication on Accounting Information Quality (not useful). Asian Journal of Information 
Technology, 14(5), 154-161. https://doi.org/10.3923/ajit.2015.154.161  

Gamayuni, R. R. (2019). The effect of management accounting information system application on 
information quality and its implication on good government governance. International 
Journal of Scientific and Technology Research, 8(8), 1247-1254. 

Garasyim, P., Bondarenko, O., Klym, N., Karpenko, Y., & Bondarchuk, L. (2020). Strategic 
management accounting of business processes of the service sector enterprises. Academy of 
Accounting and Financial Studies Journal, 24(2). Retrieved from 
https://www.scopus.com/inward/record.uri?eid=2-s2.0-
85088933686&partnerID=40&md5=93ea70fdc8567b59f5feac74fa4ee496  

Gericke, A., Klesse, M., Winter, R., & Wortmann, F. (2010). Success Factors of Application 
Integration: An Exploratory Analysis. Communications of the Association for Information 
Systems, 27(May 2014). https://doi.org/10.17705/1CAIS.02737  

Ghasemi, R., Habibi, H. R., Ghasemlo, M., & Karami, M. (2019). The effectiveness of management 
accounting systems: evidence from financial organizations in Iran. Journal of Accounting in 
Emerging Economies, 9(2), 182-207. https://doi.org/10.1108/JAEE-02-2017-0013  

Giannetti, R., Cinquini, L., Miolo Vitali, P., & Mitchell, F. (2021). Management accounting change 
as a learning process: a longitudinal analysis. Qualitative Research in Accounting & 
Management, 18(4/5), 484-515. https://doi.org/10.1108/QRAM-01-2017-0003  

Gordon, L. A., & Miller, D. (1976). A contingency framework for the design of accounting 
information systems. Accounting, Organizations and Society, 1(1), 59-69. 
https://doi.org/10.1016/0361-3682(76)90007-6  

Griffin, R. W. (2016). Management. Boston: Cengage Learning. 

Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2021). Partial Least Squares Structural Equation 
Modeling (PLS-SEM). USA: SAGE Publications. https://doi.org/10.1007/978-3-030-80519-7  

Hall, J. A. (2013). Introduction to Accounting Information Systems. South-Western: Cengage 
Learning. 

Hardika, A., Putra, I. G. S., & Halimrachmat, R. A. (2019). Characteristics of management 
accounting systems, implementation of accounting information systems and managerial 
performance. International Journal of Advanced Science and Technology, 28(6), 1-7. 
Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-
85080117351&partnerID=40&md5=b8b53c77e6b7f0e259331f27098a7c46  

Heidmann, M., Schäffer, U., & Strahringer, S. (2008). Exploring the role of management accounting 
systems in strategic sensemaking. Information Systems Management, 25(3), 244-257.  
https://doi.org/10.1080/10580530802151194  

https://doi.org/10.26905/jkdp.v25i1.5330
https://doi.org/10.1145/3444465.3444467
https://doi.org/10.3923/ajit.2015.154.161
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088933686&partnerID=40&md5=93ea70fdc8567b59f5feac74fa4ee496
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088933686&partnerID=40&md5=93ea70fdc8567b59f5feac74fa4ee496
https://doi.org/10.17705/1CAIS.02737
https://doi.org/10.1108/JAEE-02-2017-0013
https://doi.org/10.1108/QRAM-01-2017-0003
https://doi.org/10.1016/0361-3682(76)90007-6
https://doi.org/10.1007/978-3-030-80519-7
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080117351&partnerID=40&md5=b8b53c77e6b7f0e259331f27098a7c46
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080117351&partnerID=40&md5=b8b53c77e6b7f0e259331f27098a7c46
https://doi.org/10.1080/10580530802151194


 

8 

Kartiwa, J. (n.d.). Industri Tekstil RI saat Pandemi: Sudah Jatuh Tertima Tangga. Katadata.Co.Id. 
Retrieved from https://katadata.co.id/yurasyahrul/indepth/5ea7d4e5648ed/industri-
tekstil-ri-saat-pandemi-sudah-jatuh-tertimpa-tangga  

Maryanova, S., Petrovska, S., Lysenko, A., Kravchenko, M., & Metil, T. (2019). Organization of 
management accounting on the basis of the process approach automation. Academy of 
Accounting and Financial Studies Journal, 23(Special Issue 2). Retrieved from 
https://www.scopus.com/inward/record.uri?eid=2-s2.0-
85071696968&partnerID=40&md5=dd490dcbdbe10b65c1130718024140b3  

Matiukha, M., & Rovnyagin, A. (2020). Managerial Accounting As an Element of Information 
Resources Management of an Enterprise. EUREKA: Social and Humanities, 1(1), 3-9. 
https://doi.org/10.21303/2504-5571.2020.001045  

Mia, L., & Winata, L. (2008). Manufacturing Strategy, Broad Scope MAS Information and 
Information and Communication Technology. The British Accounting Review, 40(2), 182-
192. https://doi.org/https://doi.org/10.1016/j.bar.2008.02.003  

Miller, K. D. (1993). Industry and Country Effects on Managers' Perceptions of Environmental 
Uncertainties. Journal of International Business Studies, 24(4), 693-714. Retrieved from 
https://doi.org/10.1057/palgrave.jibs.8490251  

Moorhead, G., & Griffin, R. W. (2012). Organizational Behavior. South-Western: Cengage Learning. 

Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of Information and System Quality: 
An Empirical Examination Within the Context of Data Warehousing. Journal of Management 
Information Systems, 21(4), 199-235. https://doi.org/10.1080/07421222.2005.11045823  

Novianty, I. (2019). The Quality of Management Accounting Information Systems from Users 
Ethics, Environment Uncertainty and Top Management (an Empirical case of Local 
Government in Indonesia). South East Asia Journal of Contemporary Business, Economics 
and Law, 20(1), 1-10. 

Pedroso, E., Gomes, C. F., & Yasin, M. M. (2020). Management accounting systems: an 
organizational competitive performance perspective. Benchmarking: An International 
Journal, 27(6), 1843-1874. https://doi.org/10.1108/BIJ-12-2019-0547  

Prihastiwi, D. A., & Sholihin, M. (2018). Factors Affecting The Use of Management Accounting 
Practices in Small and Medium Enterprises: Evidence from Indonesia. Jurnal Dinamika 
Akuntansi, 10(2), 158-176. https://doi.org/10.15294/jda.v10i2.17307  

Rachmawati, R. (2019). Relationship between accounting information systems implementation and 
corporate governance of rural banks in Indonesia. Diponegoro International Journal of 
Business, 2(1), 10-17. https://doi.org/10.14710/dijb.2.1.2019.10-17  

Ritonga, K. (2010). Determining the Moderating Effect of Perceived Environmental Uncertainty 
Management Accounting Information Systems Relationship in Indonesia Manufacturing 
Companies. Indonesian Management & Accounting Research, 9(1), 27-43. 
https://doi.org/10.25105/imar.v9i1.1286  

Schulz, A. K. D., Wu, A., & Chow, C. W. (2010). Environmental uncertainty, comprehensive 
performance measurement systems, performance-based compensation, and organizational 
performance. Asia-Pacific Journal of Accounting and Economics, 17(1), 17-39. 
https://doi.org/10.1080/16081625.2010.9720850  

Strumickas, M., & Valanciene, L. (2010). Development of Modern Management accounting system. 
Engineering Economics, 21(4), 377-386. https://doi.org/10.5755/j01.ee.21.4.11710  

https://katadata.co.id/yurasyahrul/indepth/5ea7d4e5648ed/industri-tekstil-ri-saat-pandemi-sudah-jatuh-tertimpa-tangga
https://katadata.co.id/yurasyahrul/indepth/5ea7d4e5648ed/industri-tekstil-ri-saat-pandemi-sudah-jatuh-tertimpa-tangga
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071696968&partnerID=40&md5=dd490dcbdbe10b65c1130718024140b3
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071696968&partnerID=40&md5=dd490dcbdbe10b65c1130718024140b3
https://doi.org/10.21303/2504-5571.2020.001045
https://doi.org/https:/doi.org/10.1016/j.bar.2008.02.003
https://doi.org/10.1057/palgrave.jibs.8490251
https://doi.org/10.1080/07421222.2005.11045823
https://doi.org/10.1108/BIJ-12-2019-0547
https://doi.org/10.15294/jda.v10i2.17307
https://doi.org/10.14710/dijb.2.1.2019.10-17
https://doi.org/10.25105/imar.v9i1.1286
https://doi.org/10.1080/16081625.2010.9720850
https://doi.org/10.5755/j01.ee.21.4.11710


 

9 

Susanto, A., & Meiryani. (2019). How quality of management accounting information systems is 
influenced by environmental complexity? International Journal of Innovation, Creativity and 
Change, 5(2), 909-922. 

Ugalde, F., & Naranjo-gil, D. (2020). Management Accounting Systems, Top Management Teams, 
and Sustainable Knowledge Acquisition: Effects on Performance. Sustainability 
(Switzerland), 1-14.