Employing a hierarchical data envelopment analysis to evaluate the competitiveness of listed companies in Indonesia

Financial system stability is not only supported by the banking sector, but also the role of insurance companies that operate efficiently. The study aims to analyze the efficiency performance of general insurance companies using two stages of data envelopment analysis during the 2017 – 2018 period. The first stage of efficiency measurement using a non-parametric data envelopment analysis (DEA) approach shows the efficiency level of general insurance companies experiencing a positive trend. The performance of general insurance companies in 2018 was more efficient than in 2017 based on the value of technical efficiency (CRS) and the value of pure technical efficiency (VRS). This means that in general there has been an increase in the efficiency of general insurance companies in Indonesia from 2017 to 2018. Testing the efficiency determinants in the second stage using the Tobit regression model found that the cost ratio is the only factor that significantly influences the efficiency level of general insurance companies in Indonesia. Meanwhile, company ownership and investment adequacy ratio have no significant effect on the efficiency level of general insurance companies in Indonesia. The results of the study provide recommendations to the management of general insurance companies that efficiency performance has not reached the maximum, and to improve it, it is necessary to control costs without disturbing routine operations and development activities.

This study focuses on measuring the performance of life insurance companies in Indonesia and Malaysia. Input oriented Data Envelopment Analysis (DEA) uses panel data to extract the efficiency score of 5 life insurance companies from Indonesia and 5 life insurance companies from Malaysia for the year of 2015-2019. DEA-based Malmquist Total Factor Productivity (TFP) Index used to measure the efficiency change along the study period. This study utilizes asset and operating expenses as input variables, as for output variables, this study utilizes premium and investment income. Based on an efficiency score computed by DEA, most of the life insurance companies in both countries perform efficiently during the study period. However, life insurance companies in Indonesia still perform more efficiently than Malaysian life insurance companies. The results of the Malmquist TFP Index for life insurance companies in both countries show that there is 2.5% improvement in technical efficiency change, 1.5% deterioration in technology efficiency change, 0.6% improvement in pure efficiency change, 1.9% improvement on scale efficiency change, and 0.9% increase in TFP change. It shows that the main reason for TFP increased is due to improvement of technical efficiency change.


 Purpose – The purpose of this study is to analyze the efficiency level of sharia general insurance in Indonesia.
 Methodology/approach – This study uses the Data Envelopment Analysis (DEA) method with output orientation. The objects in this study were 8 general insurance companies in Indonesia during the 2015-2020 period. The variables used consist of input variables (total assets, capital/equity, operating expenses, claim payments) and output variables (investment income, tabarru' funds, profit).
 Findings – There are three Sharia General Insurance Companies in efficient condition during the study period, namely Allianz Utama Indonesia Insurance, Sinar Mas Insurance, and Bumiputeramuda General Insurance. In addition, there were five companies in an inefficient condition during the study period, namely PT Asuransi Bringin Sejahtera Artamakmur, PT Asuransi Ramayana, PT Asuransi Staco Mandiri, PT Asuransi Umum Mega, and PT Asuransi Wahana Tata.
 Novelty/value – The contribution of this research is to provide an efficiency analysis of Sharia General Insurance companies in Indonesia using several inputs and outputs. Keywords Efficiency, Islamic Insurance, Data Envelopment Analysis (DEA).

This study aims to analyze the efficiency of the performance of finance companies in Indonesia during the COVID-19 pandemic starting from 2019-2021 using the Data Envelopment Analysis (DEA) approach. The type of data in this research is secondary data in the form of financial statements and annual reports of finance companies obtained from the official websites www.idx.co.id and www.ojk.go.id. The population in this study were all finance companies in Indonesia registered with the financial services authority (OJK). The sampling technique used is purposive sampling technique with a sample of 76 finance companies. The test used in this study is a non-parametric test with a Data Envelopment Analysis (DEA) model that compares the inputs and outputs of companies. The selected input variables include, fixed assets, labor costs, third party funds (DPK). While the output variables include loans, interest income, non-interest income. The results showed that the average finance company in 2019 had an efficient value and continued to increase, but at the beginning of 2020 to 2021 it experienced an inefficient decline during the covid-19 pandemic

Along with the increase in government programs to accelerate infrastructure development, the construction industry in Indonesia has faced intense competition which has forced construction companies in Indonesia to be efficient in order to remain profitable. This study is aimed to measure the efficiency of construction companies in Indonesia. Data Envelopment Analysis (DEA)is used for the research method and data is obtained from the companies’ yearly report in the period 2010-2016 listed in the Indonesia Stock Exchange. The results of the study show that state-owned enterprises (BUMN) are more efficient than private companies. This is due to the large number and value of the project from the government in the field of infrastructure. The study has important implications for the the government to warn state owned companies to stay efficient yet profitable when facing foreign competitions. Since the study showed that companies with large revenue (sales) and low cost are efficient. The private companies ought to seek bigger sales from government projects

The purpose of this study is to estimate the efficiency level of Islamic insurance companies in Indonesia. The data used are taken from each financial report of 14 Islamic life insurance companies and 12 Islamic general insurance in the period 2013-2015. Efficiency score estimation is done by using Data Envelopment Analysis (DEA) method. There are three input variables, namely asset, load, claim payment and two output variables, namely income and tabarru’ funds obtained. The results show that islamic life insurance and islamic general insurance companies in Indonesia have not been operating efficiently.

This study aims to capture the efficiency level of industry players in conventional joint venture life insurance companies in Indonesia before and during the Covid-19 pandemic. Efficiency is related to the level of success of an activity being assessed in terms of the ratio between amounts of the output generated and the input used to generate the outputs in the activity. Efficiency can be measured using the Data Envelopment Analysis (DEA) method, which is a non-parametric frontier approach that uses mathematical programming with 2 (two) assumptions, namely Constant Return to Scale (CRS) and Variable Return to Scale (VRS). The variables used are input and output variables, wherein the input variables include total debt, labor costs, claims expenses, investment composition of stocks, bonds, and securities issued by the government of the Republic of Indonesia (RI). The output variables used are premium income and investment returns. The type of data used is secondary data. The data collection technique used is library research. The objects used as samples were top 10 (ten) conventional joint venture life insurance companies in terms of revenues with the data obtained from the financial reports and annual reports of each company for the period between 2015 and 2021. The analysis show that investment portfolio performances derived from the company strategy acts as the main efficiency determinant in the industry.

Studying the optimal subsection of distribution networks feeders, a subsection scheme synthesizing load and the length of subsections is presented. Hierarchical data envelopment analysis (DEA) method is proposed for multi-objective evaluation of subsection schemes. First, the scientific assessment system is established by using the analytic hierarchy process (AHP) and the weights of assessment criteria are derived from the judgment matrix. Secondly, the actual index data is used to structure DEA model, the schemes are evaluated quantificational with regard to different assessment criteria. Finally, each scheme is evaluated comprehensively. Using this method and the evaluation system to evaluate the subsection schemes, the evaluation results show that the assessment method is scientific and effective; the subsection method presented in this paper can better meet the economic and reliability requirements and is simple and practical.

In order to gather information on business decisions and to evaluate the economy and efficiency of current operations, companies require performance evaluation. In the absence of standards or benchmarks for assessment, performance evaluation plays a crucial role in enhancing the business's operational procedures. Data envelopment analysis (DEA) is a tool for measuring performance. The objectives of this study are to measure the efficiency of warehousing, expedition, and courier companies using the input-oriented DEA envelopment model; to analyze the DEA efficiency scores of each decision-making unit (DMU); to identify the efficient and inefficient status of each DMU; and to provide recommendations for development strategies to improve the efficiency of these companies. The results of the study indicate that the inefficient DMU has a presentation of 60%. This value is 20% greater than the efficient DMU (40%). Based on the fluctuation of DEA efficiency score distribution in each DMU, there are 6 DMU efficiency groups. These are Group 1 (ES = 1, Very Efficient), Group 2 (ES = 0.90 - 0.99, Highly Efficient), Group 3 (ES = 0.80 - 0.89, Quite Efficient), Group 4 (ES = 0.60 - 0.79, Less Efficient), Group 5 (ES = 0.41 - 0.59, Inefficient), and Group 6 (ES = 0 - 0.40, Very Inefficient). Group 1 ranks first with the largest percentage (40%). The second and third ranks are Group 3 (30%) and Group 4 (20%). The fourth rank is Group 2 (1%). This study does not have DMU with 2 efficient categories, namely: Group 5 and Group 6.

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The Sharia insurance industry in Indonesia has demonstrated robust growth, bolstered by increasing public literacy in Islamic finance. However, operational efficiency remains a critical challenge in achieving sustainable competitiveness. This study aims to assess the technical efficiency of Sharia insurance companies in Indonesia through a Data Envelopment Analysis (DEA) approach. The analysis includes eleven Sharia-compliant insurers—both general and life insurance units—over the period 2015 to 2019. An input-oriented DEA model with Variable Returns to Scale (VRS) was employed, using total assets, administrative expenses, and claims paid as inputs, and premium income along with investment income as outputs. The findings indicate that only a select few companies, such as Tokio Marine and Panindai-Ichi, consistently reached optimal efficiency levels. In contrast, firms like ACA and Prudential exhibited fluctuating and relatively low efficiency. Notably, 2017 marked the highest average efficiency across all companies. These insights highlight the need to optimize cost structures, adopt effective Sharia-compliant investment strategies, and advance operational digitalization to improve overall industry efficiency.Keywords: Efficiency, Sharia Insurance, Data Envelopment Analysis, DEA, Islamic Finance Industry

This study aims to determine the level of efficiency of Sharia life insurance in Indonesia and Malaysia during the 2015-2018 period. The sample used was 12 Sharia life insurance companies in Indonesia and 5 Sharia life insurance companies in Malaysia. The method used in this research is Data Envelopment Analysis (DEA) with the assumption of Variable Return to Scale (VRS) with input-orientation. The selection of variables uses a value-added approach with its input variables, namely capital, total expenses, and total investment as well as its output variables, namely total profit and total investment income. The results of this study indicate that the average overall value of sharia life insurance efficiency in Indonesia is relatively lower than the average efficiency of sharia life insurance in Malaysia. The development trend of the efficiency of Sharia life insurance in Indonesia and Malaysia tends to decrease during 2015-2018. Meanwhile, the cause of inefficiency in Sharia life insurance in Indonesia and Malaysia is the total expenses variable. Keywords: Efficiency, Sharia Life Insurance, DEA

It is a fact that financial institutions among Asian countries, especially Indonesia, have been dominated by commercial banks. In addition, an insurance market share is only 10 percent of the financial market. Yet, the insurance industry is an important partner for the banking industry. This function is to guarantee the risk of banks in distributing credit and supporting the national economy through the community's fund. This paper evaluates the relative efficiency of 23 Non Life Insurance companies in Indonesia, using Data Envelopment Analysis (DEA) model. DEA is a management evaluation tool that assists in identifying the most efficient and inefficient decision-making units (DMUs) in the best practice frontier. Empirical results show that bigger insurance companies are found to be more efficient than smaller firms. Moreover, companies with captive market and the company's group with non-captive market have relatively the same result. These findings are new empirical contributions to efficiency literature of the insurance industry. The paper also provides policy implications for the Indonesian insurance sector.

The purpose of this study is to measure the efficiency of conventional and sharia life insurance companies in indonesia during the period 2012-2016 and to find out whether there are differences in efficiency between conventional and sharia life insurance companies. This research is a quantitative descriptive research using secondary data sourced from the company's annual financial statements. The samples used were 10 conventional life insurance companies and 10 sharia life insurance companies. Efficiency measurement in this study uses the Data Envelopment Analysis (DEA) method based on CCR model with an value-added approach. The input variables used are assets, capital, general and administrative costs, and commission expenses. While the output variable is premium and investment income. The results of this study indicate that conventional life insurance companies have a better level of efficiency than sharia life insurance companies, but there is no significant efficiency difference between conventional life insurance companies and sharia life insurance companies during the 2012-2016 period.

This study aims to investigate the efficiency performance of energy companies, especially the environmental disclosure variable as the energy companies' responsibility to the environment, especially in achieving the SDGs. In addition, several other factors were also tested to determine their effect on the level of efficiency. The study was conducted on 42 energy companies in Indonesia for the period 2018 to 2021. Efficiency analysis uses Data Envelopment Analysis with input and output variables from each financial report. Meanwhile, STATA software was used to analyze the regression. The results show that the efficiency level of gas and oil companies is more optimal than other companies. However, coal companies are better at predicting the level of efficiency. This is in line with the huge energy potential in Indonesia that comes from coal. Another finding is that although environmental disclosure has not succeeded in increasing efficiency performance, it can moderate the relationship between size and efficiency level.