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The purpose of this study is to assess empirically how the technical efficiency scores for 43 sub-sectors and their determinants over the period 2010 to 2017 show significant variation across the sub-sectors. The study applied a two-step approach for measuring technical efficiency and its determinants. A data envelopment analysis output-orientation...
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... do the analysis, 2015 and 2017 observations were taken, assuming the sub-sectors are operating in the same environment and market. The results presented in Table 4 and 5 indicates, on average, private-owned sub-sectors had registered better total technical efficiency (0.821), PTE (0.939) and SE (0.876) than public-owned sub-sectors and they are relatively efficient. When comparing subsector to sub-sector, public-owned food products and beverages and machinery and equipment are efficient both under CRS and VRS models, whereas the same sub-sectors under private ownership are inefficient. ...Citations
... According to Erena, Kalko, and Debele (2021), efficiency is producing maximum output at a given level of technology. In Ethiopia technical efficiency is the main problem, which indicates that many enterprises need to operate more efficiently across the country; either a firm is capital or labour-intensive. ...
... Previously few studies were conducted on the efficiency of MSEs. For instance, Girma, Dinka, and Gelan (2019), Leza, Rajaan, and Kuma (2019) and Erena, Kalko, and Debele (2021). Those studies focus more on the DEA approach, specific sectors, and limited areas. ...
... The above studies do not include the main factors contributing to technical efficiencies like a business plan, workplace place, social network, government support, and location. For instance, Setiawan et al. (2019), Ajibefun and Daramola (2003) and Erena, Kalko, and Debele (2021) don't incorporate variables like social network, working area location, and government support in their study. The current study contributes to the existing literature by offering a more extensive analysis and incorporating additional variables into the model. ...
Micro and small enterprises (MSEs) play a crucial role in Ethiopia’s economy. Measuring the technical efficiency ofenterprises is thus of interest to various stakeholders. This study measured and estimated technical efficiency using astochastic frontier and a maximum-likelihood approach to measure factors that determine the efficiency of enterprises.The study relied on primary data from a sample of operators collected through survey questionnaires. A multistagesampling technique was utilized to select respondents, and cross-sectional data were collected from 357 operators. The results show that operators’ technical efficiency is roughly 72.3%, indicating that with existing technology, there isroom to raise efficiency levels by an average of 28.1%; other factors remaining constant. The results from maximumlikelihood estimation show that education level, experience level, initial investment, business plan, governmentsupport, MSE location, and motivation significantly and negatively affect technical inefficiency. In contrast, variableslike other sources of income affect technical inefficiency positively. The study suggests that governmental support is crucial, with an emphasis on providing sufficient initial funding. Moreover, there is a need to offer training in businessplan development and to facilitate an increase in educational standards. Additionally, careful consideration should be given to selecting optimal operational locations.
... The Stochastic frontier production function model was utilized to determine the technical efficiency of Binadhan-17 growers in the study areas (Erena et al., 2021). The model function is specified as below, ...
The Haor region contributes approximately 20% of Bangladesh’s total rice production, and this study focused on the Binadhan-17 rice variety in three key Haor districts including, Sunamganj, Kishoreganj, and Netrokona. The research aimed to assess the costs, returns, and technical efficiency of Binadhan-17 cultivation, surveying 180 randomly selected farmers from the region. Using a stochastic frontier production function model and descriptive statistics, the study found that the average production cost per hectare was BDT 76,863, with fixed costs accounting for 35.90% and variable costs for 64.10%. The average net return per hectare was BDT 44,289, and the Benefit-Cost Ratio (BCR) was 1.58, with Sunamganj having the highest BCR (1.62), followed by Kishoreganj (1.57) and Netrokona (1.54). Significant positive relationships were found between human labor, land preparation, and insecticide costs at the 1% level, while seed, urea, and organic manure costs were significant at the 10% level, and TSP was significant at the 5% level. Around 68.33% of farmers achieved outputs close to the maximum frontier level (91%–99%), with an average technical efficiency of 89.40%, indicating a 10.60% production loss due to inefficiency. The study also identified several challenges faced by farmers, including difficulties in obtaining timely seed and labor, limited knowledge of production technologies, high fertilizer prices, and lack of capital, offering insights for policymakers to enhance rice production in the short term. Asian Australas. J. Food Saf. Secur. 2024, 8(2), 58-66
... In production activities are said to be efficient if the scale of return is increasing or at least constant. A micro waqf bank is a business unit that manages waqf According to [4], efficiency is the best comparison between inputs (inputs) and ...
... Allocative Efficiency (AE) is the ability of a company (farm) to use inputs in optimal proportion at a given price and production technology. The combination of these two efficiencies is called economic efficiency (EE) or total efficiency [3], [4]. ...
... Opinion[9] states that efficiency is a measure of the amount of collection of costs used to generate revenue. Effective management (effective operation) optimizes the use of available resources to achieve the desired goals to the maximum, and does not waste available resources in the implementation of its activities[4]. ...
In the observation period from 2018 to 2021, the growth of outstanding financing only grew 6.5% per year and the number of outstanding customers grew 4.91% per year, while the number of stagnant micro waqf banks did not grow at 62. Therefore, it is urgent to measure the efficiency and productivity of micro waqf banks so that the source of the causes of the suboptimal distribution of micro waqf bank financing to the community around the pesantren can be evaluated. Technical analysis with DEA and Malmquist Index was used to measure the efficiency and productivity. The input data used are the number of outstanding customers, the number of Kumpi, and the number of micro waqf bank offices. Output data uses the amount of outstanding financing. Micro waqf banks that have consistently been inefficient from 2018 to 2021 are waqf banks in Riau and West Java Provinces. The inefficient waqf bank according to this approach is only 27.75. Overall, micro waqf banks have very low technological innovation. Optimization of micro waqf bank financing can still be done by optimizing the function of micro waqf banks and activating micro waqf bank partners who have been passive. Keywords: efficiency, productivity, technology, Waqf Bank
... Technical efficiency is important for the improvement and development of modern industries and contributing to the country's economy and are the focus of policy issues in many countries (Tamirat, N., & Tadele, S., 2023). Technical efficiency is a leading indicator, as such, measures ultimate performance of industries (Erena, O. et al., 2021;Nishanthini, A., & Nimalathasan, B., 2013). It helps the industries to underset and scale and scope of their activity and enables them to position and take appropriate actions to stay competitive in the market. ...
... Kumbhakar and Lovell (2003), also specified that technical efficiency is the ability to reduce the use of inputs to produce outputs or the ability to maximize output with existing input. Meanwhile, allocative efficiency reflects the firm"s ability to use inputs at an optimal rate based on the cost and production technology (Erena, O. et al., 2021;Fikadie, D., 2022). These measures are combined to provide a measure of the total economic efficiency (Jofree, A. et al., 2021). ...
... Among the fundamental economic problems that faces less developed countries, including Ethiopia, are their economies' backwardness and lack of efficient resources utilization to support their desire and drive (Bekele, T., & Belay, K., 2007). It is widely stated that technical inefficiency challenging the industrial sectors of the countries including wood industries (Erena, O. et al., 2021). According to Abuka (2005) Efficiency levels vary between industries and over time within the same industry. ...
Technical efficiency is crucial for the advancement and growth of contemporary enterprises and is a major area of policy concern in many countries. Numerous pieces of evidence suggest that Ethiopia's industries, particularly those depend on wood were not operating as efficient as they should be. As a result, the country is not benefiting as much from the sector as it ought to, and it is now compelled to import wooden products at a higher cost in foreign exchange. Therefore, to examine the technical efficiency of the industries; four purposively selected main cities such as Addis Ababa, Hawassa, Jima and Bahir Dar were selected. From these cities, information was collected, analyzed, and the results were obtained. The result shows that the technical efficiency of Ethiopia's wood industries is lower than expected. Out of a total of 170, about 149 (87.6 %) of the furniture workshops are technically inefficient. This is because workers working in the wood industries are less educated. In addition to this lack of on-the-job training, lack of modern machineries and insufficient skills to use them properly, inconvenient production and sales area, shortage and quality of raw materials, insufficient capital, lack of market connection, have been shown to be the reasons. Therefore, to improve the technical efficiency of the industries, it is better to have continuous vocational training, loan support so that they can get and use better machines, as well as convenient manufacturing, product display and sales, improving and facilitating market linkages.
... Furthermore, how fast the innovation is invented depends on the integration of research activities and human capital contributing to the acceleration of absorptive capacity for new knowledge creation as well as mimic of others (Cohen & Levinthal, 1990; Männasoo et al., 2018). This process of knowledge creation and innovation is then used for firms to improve not only technological progress but also the managerial skills and technical knowledges, which are captured by technical efficiency indicator (Erena et al., 2021), and altogether improving country's productivity, as suggested by Farrell (1957) (see Figure 1 for the framework illustration). In this sense, the standard classical assumption that neglects the possible slack of production due to different managerial competencies is no longer pertinent. ...
The impact of research and development (R&D) spending has been shown significantly in promoting country’s economic growth and productivity. Hence, we examine the research question by employing Indonesian manufacturing firm-level dataset in the years of 2017–2019 and by using Stochastic Frontier Analysis (SFA) to reveal whether heterogeneous firm’s R&D spending contributes to the efficiency performance of the company. The finding reveals the robust positive effect of R&D spending to the efficiency performance, which implies that firms allocating more R&D spending will perform better efficiency due to, for example, managerial expertise improvements. An interesting finding is shown by the interaction model for which larger R&D allocated by foreign firm will boost better efficiency than that allocated by domestic firms, supporting prior arguments that foreign firm can be the driver of innovation as they are more likely to be closer to the world technology frontier. Several policy implications are suggested such as in-house R&D program to encourage human capital development and tax incentive to avoid market rivalry with foreign firms.
... Technical efficiency is important for the improvement and development of modern industries and contributing to the country's economy and are the focus of policy issues in many countries (Tamirat, N., & Tadele, S., 2023). Technical efficiency is a leading indicator, as such, measures ultimate performance of industries (Erena, O. et al., 2021;Nishanthini, A., & Nimalathasan, B., 2013). It helps the industries to underset and scale and scope of their activity and enables them to position and take appropriate actions to stay competitive in the market. ...
... Kumbhakar and Lovell (2003), also specified that technical efficiency is the ability to reduce the use of inputs to produce outputs or the ability to maximize output with existing input. Meanwhile, allocative efficiency reflects the firm"s ability to use inputs at an optimal rate based on the cost and production technology (Erena, O. et al., 2021;Fikadie, D., 2022). These measures are combined to provide a measure of the total economic efficiency (Jofree, A. et al., 2021). ...
... Among the fundamental economic problems that faces less developed countries, including Ethiopia, are their economies' backwardness and lack of efficient resources utilization to support their desire and drive (Bekele, T., & Belay, K., 2007). It is widely stated that technical inefficiency challenging the industrial sectors of the countries including wood industries (Erena, O. et al., 2021). According to Abuka (2005) Efficiency levels vary between industries and over time within the same industry. ...
Technical efficiency is crucial for the advancement and growth of contemporary enterprises and is a major area of policy concern in many countries. Numerous pieces of evidence suggest that Ethiopia's industries, particularly those depend on wood were not operating as efficient as they should be. As a result, the country is not benefiting as much from the sector as it ought to, and it is now compelled to import wooden products at a higher cost in foreign exchange. Therefore, to examine the technical efficiency of the industries; four purposively selected main cities such as Addis Ababa, Hawassa, Jima and Bahir Dar were selected. From these cities, information was collected, analyzed, and the results were obtained. The result shows that the technical efficiency of Ethiopia's wood industries is lower than expected. Out of a total of 170, about 149 (87.6 %) of the furniture workshops are technically inefficient. This is because workers working in the wood industries are less educated. In addition to this lack of on-the-job training, lack of modern machineries and insufficient skills to use them properly, inconvenient production and sales area, shortage and quality of raw materials, insufficient capital, lack of market connection, have been shown to be the reasons. Therefore, to improve the technical efficiency of the industries, it is better to have continuous vocational training, loan support so that they can get and use better machines, as well as convenient manufacturing, product display and sales, improving and facilitating market linkages.
... Technical efficiency involves firms' ability to produce maximum outputs from a given production vector, and is measured by the output-input ratio (Coelli, 1996). Erena et al. (2021) state that, given technological innovation, technical efficiency is firm's ability to increase output level with a given level of productive inputs. ...
The essence of electricity sector reform is to improve the technical efficiencyof power utilities, thereby increasing access to reliable electricity and the productive use of electricity. In this light, this study examines the impact of electricity sector reform on the efficiency of distribution companies (DisCOs) in Nigeria. The study employs panel data from 11 DisCos between 2012 and 2020 and the Translog Input Distance Function of Stochastic Frontier Analysis (SFA) with Maximum Likelihood (ML) random-effects time-varying model of technical inefficiencies. In terms of the distribution of the inefficiency term, the truncated normal distribution, which allows the use of a single-step procedure to examine the impact of exogenous factors (electricity sector reform) on the inefficiency of the DisCOs is employed. The paper finds that electricity sector reform has a significant relationship with the efficiency of DisCOs. The presence of regulation further decreases the sub-sector's efficiency; however, private sector involvement in the sub-sector improves the distribution companies' efficiency. The impact of competition on DisCOs' efficiency is inconclusive. The study finds DisCOsto be highly inefficient despite sector reforms, with an average efficiency of 23 percent, which is remarkably low for a privatized industry. The paper therefore concludesthat electricity sector reform did not result in the desired efficiency gains of the DisCos. The study therefore recommends that more private sector involving is needed to improve the efficiency of the distribution sub-sector, with government involvement limited to supervisory or regulatory role.
... Technical efficiency involves firms' ability to produce maximum outputs from a given production vector, and is measured by the output-input ratio (Coelli, 1996). Erena et al. (2021) state that, given technological innovation, technical efficiency is firm's ability to increase output level with a given level of productive inputs. ...
The essence of electricity sector reform is to improve the technical efficiencyof power utilities, thereby increasing access to reliable electricity and the productive use of electricity. In this light, this study examines the impact of electricity sector reform on the efficiency of distribution companies (DisCOs) in Nigeria. The study employs panel data from 11 DisCos between 2012 and 2020 and the Translog Input Distance Function of Stochastic Frontier Analysis (SFA) with Maximum Likelihood (ML) random-effects time-varying model of technical inefficiencies. In terms of the distribution of the inefficiency term, the truncated normal distribution, which allows the use of a single-step procedure to examine the impact of exogenous factors (electricity sector reform) on the inefficiency of the DisCOs is employed. The paper finds that electricity sector reform has a significant relationship with the efficiency of DisCOs. The presence of regulation further decreases the sub-sector's efficiency; however, private sector involvement in the sub-sector improves the distribution companies' efficiency. The impact of competition on DisCOs' efficiency is inconclusive. The study finds DisCOsto be highly inefficient despite sector reforms, with an average efficiency of 23 percent, which is remarkably low for a privatized industry. The paper therefore concludesthat electricity sector reform did not result in the desired efficiency gains of the DisCos. The study therefore recommends that more private sector involving is needed to improve the efficiency of the distribution sub-sector, with government involvement limited to supervisory or regulatory role.
... It is because technical efficiency is the capability and ability of firm or industry to produce the maximum output by using available inputs as well as technologies in production (Kea et al., 2016). Besides, Erena et al., (2021) also expressed that total factor productivity (TFP) growth can be generated by efficiency improvement in the production. In fact, technical efficiency particularly in fully utilize the existing inputs include technologies and labor to produce maximum outputs for ASEAN deserved even more attention by the scholar as ASEAN was hits by the inflation in terms of input price in ...
As labor oriented economies, ASEAN not only consistently suffer a subpar performance in terms of productivity growth compare to other countries in Asia since 1987 but also facing elderly population problem which closely related to Sustainable Development Goals (SDG 8). Hence, this study investigates the impacts of elderly population on the technical efficiency of ASEAN over the period of 1990–2019. The estimated technical efficiency for ASEAN collectively reached 0.7398 with Myanmar in highest and Lao PDR in lowest position. Besides, elderly population was proven negatively and significantly influences the technical efficiency of ASEAN. In depth, 1% increment in elderly population will decrease 3.4% of the estimated technical efficiency of ASEAN. Surprisingly, crude death rate is significantly and positively influences the technical efficiency of ASEAN. It depicted that the growth of population may not able to be transformed as the skilled workers in ASEAN. While labor force participation of the elderly is a current trend in ASEAN, the member states of ASEAN particularly Brunei and Myanmar are suggested to carry out more policies such as providing more ICT skill training and job reallocation based on physical ability to improve the productivity among the elderly labor.
... This finding is also in agreement with a study done in Ethiopia which suggests that shortage of raw materials was the main cause of the relative technical inefficiency of the sector (Erena, Kalko, & Debele, 2021;Hailu & Tanaka, 2015). Another study in Nigeria by Ekwochi, Ejim, and Agbaji (2021) found that working capital management has an impact on the productivity of manufacturing. ...
Most manufacturing industries in Ethiopia are not operating at full capacity. The manufacturing industry is one of the main determinants of the economic growth of a country; therefore, the reasons why they are not operating at full capacity have to be assessed. The aim of this study is to assess determinant factors associated with Ethiopia’s large and medium manufacturing industries (henceforth referred to as LMMIs in this study) not working at full capacity based on 2020 LMMI survey data. In this study, 3,067 large and medium manufacturing industries were examined. Among these industries, 78.71% were not working at their full capacity, while the remaining 21.29% were. Binary logistic methods were used to analyze the data. Study results found that the region, the number of months the establishment operated during the study period, the workplace of the manufacturing company, the effect of Covid-19, and the current most serious problem facing the establishment were statistically significant predictors for working at full capacity. LMMI intervention programs, including regional work, increasing the number of working months in the year, workplace, the effect of unexpected external influences (e.g., COVID-19) and major problems among LMMIs, should be put in place to increase the production to full capacity.
