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Introduction: The unique characteristics of pineapples as a perennial plant, which guarantee their quick proliferation and adoption in both the tropics and subtropics, readily justify their economic significance. Although pineapple is a popular tropical fruit among Bangladeshi citizens, they continue to produce fewer pineapples than other international producers with limited export offerings. Hence, the study aimed to estimate the technological efficiency, prospects, and policies of pineapple growers in the northeastern district of Bangladesh. Methods: One hundred respondent growers were surveyed directly to gather cross-sectional data using a multistage sampling technique. The technical efficiency scores of individual farms were calculated using the stochastic frontier model with the technical inefficiency model for identifying factors responsible for inefficiency. Results: The technical efficiency scores range from about two-thirds to the absolute efficiency level, with a mean technical efficiency above the ninety percent level. The technical inefficiency effect model interpreted that farmers' age and education had a significant positive impact, whereas credit, training, and family size had a significant negative impact on inefficiency. Discussion: Findings indicated that sampled farmers may use inputs more efficiently and raise their yield by nearly one-twentieth. Therefore, the study suggests that the government should concentrate on strategies to attract young growers, as they are more capable of managing resources effectively and willing to accept technological breakthroughs. The study's conclusions have significant policy ramifications specifically in the areas of finance, education and skills, and rural development that the Government should consider to increase farmer's productivity and overcome various challenges while upholding national interests and ensuring the farming sector's continued prosperity. To commercialize pineapple production and establish Bangladesh as a prominent production zone, more research and development are needed. [ABSTRACT FROM AUTHOR]

Persistent electricity shortages in Pakistan, causing prolonged grid power load shedding, have adversely impacted various sectors, notably agriculture and the livelihoods of rural farmers. Literature suggests that adopting photovoltaic solar energy can mitigate these issues. This research aims to measure the impact of photovoltaic solar energy on the technical efficiency of food productivity in Khyber Pakhtunkhwa, Pakistan, applying data from 580 respondents. Addressing self-selective bias through ESR and stochastic frontier production function model is utilized to assess technical efficiency. The findings of this study reveal that farmers using solar energy experience a significant improvement in technical efficiency, with 15.8 percent of them achieving a 7.643 percent increase, after accounting for self-selection bias. Furthermore, the positive effects are more pronounced among larger farms and those with greater farming experience. This study underscores the importance of evidence-based approaches in implementing solar energy solutions, highlighting their potential to foster sustainability and equitable development at the grassroots level. The research culminates with policy recommendations that underscore the importance of promoting the photovoltaic solar energy use among farmers to improve food security and increase agricultural productivity. [ABSTRACT FROM AUTHOR]

Introduction: There is a global priority to ensure food security, environmental conservation and sustainability. The adoption of inputs such as organic manures, biofertilisers, and biopesticides has been widely promoted as a way to enhance agricultural sustainability, yet their adoption rates remain notably low. The study examines the determinants and impact of the adoption of multiple sustainable inputs by paddy farmers in India. The study also examines the drivers behind the intensity of their adoption and their technical efficiency. Methods: The study utilises the survey dataset on paddy farmers from "Situation Assessment of Agricultural Households and Land and Livestock Holdings of Households in Rural India" of the 77th National Sample Survey (NSSO) round. The reference period for data collection was the agricultural year from July 2018 to June 2019. The analytical methods employed include the Multivariate Probit and Ordered Probit models, Seemingly Unrelated Regression, Regression Adjustment model, and Stochastic Frontier method. Results: The empirical findings reveal that the adoption and intensity of sustainable inputs depend significantly on factors such as the household head's age and education, household size, and access to extension services. Adopting sustainable inputs has significant benefits, such as increased harvest value. However, the currently available technical advisory services are limited in effectively promoting the expenditure on sustainable inputs. Technical efficiency analysis underscores the potential for improvement and the importance of utilising optimal input levels. The research findings provide strong evidence in favour of advocating for the use of sustainable inputs in paddy farming. [ABSTRACT FROM AUTHOR]

Background: Priority-setting becomes more difficult for decision-makers when the demand for health services and health care resources rises. Despite the fact that the Ethiopian healthcare system places a strong focus on the efficient utilization and allocation of health care resources, studies of efficiency in healthcare facilities have been very limited. Hence, the study aimed to evaluate efficiency and its determinants in public health centers. Methods: A cross-sectional study was conducted in the East Wollega zone, Oromia Regional State, Ethiopia. Ethiopian fiscal year of 2021–2022 data was collected from August 01–30, 2022 and 34 health centers (decision-making units) were included in the analysis. Data envelope analysis was used to analyze the technical efficiency. A Tobit regression model was used to identify determinants of efficiency, declaring the statistical significance level at P < 0.05, using 95% confidence interval. Results: The overall efficiency score was estimated to be 0.47 (95% CI = 0.36–0.57). Out of 34 health centers, only 3 (8.82%) of them were technically efficient, with an efficiency score of 1 and 31 (91.2%) were scale-inefficient, with an average score of 0.54. A majority, 30 (88.2%) of inefficient health centers exhibited increasing return scales. The technical efficiency of urban health centers was (β = -0.35, 95% CI: -0.54, -0.07) and affected health centers' catchment areas by armed conflicts declined (β = -0.21, 95% CI: -0.39, -0.03) by 35% and 21%, respectively. Providing in-service training for healthcare providers increased the efficiency by 27%; 95% CI, β = 0.27(0.05–0.49). Conclusions: Only one out of ten health centers was technically efficient, indicating that nine out of ten were scale-inefficient and utilized nearly half of the healthcare resources inefficiently, despite the fact that they could potentially reduce their inputs nearly by half while still maintaining the same level of outputs. The location of health centers and armed conflict incidents significantly declined the efficiency scores, whereas in-service training improved the efficiency. Therefore, the government and health sector should work on the efficient utilization of healthcare resources, resolving armed conflicts, organizing training opportunities, and taking into account the locations of the healthcare facilities during resource allocation. [ABSTRACT FROM AUTHOR]

Background: Medical diagnostic laboratories are an essential work environment that plays an important role in diagnosing, treating, and being sensitive to diseases. One way to evaluate laboratories' performance is to calculate their efficiency. This study investigates the efficiency of laboratories that are related to health centers in the south of Iran. Methods: This study was conducted in 2021. The input numbers include: the number of technical personnel and the number of cell counters, and the output data includes: the scores obtained from the level 2 health laboratory evaluation list. And efficiency was calculated with DEAP software. The analysis is accomplished by the assumption of input-oriented. Findings: The efficiency of laboratories of Orzueeyeh and Ravar Cities had the highest efficiency with the assumption of variable returns to scale efficiency 1, and the model of all laboratories is the laboratory of Ravar City. The laboratories of Kuhbanan and Rabor cities had the lowest efficiency with the assumption of variable returns to scale efficiency of 0.859 and 0.899, respectively. The average scale efficiency, Variable returns to scale, and constant returns to scale for laboratories in the cities of Kerman province are 0.842, 0.943, and 0.895, respectively. Conclusions: To increase the efficiency of laboratories, significant resources and funds should be used, as well as few studies have been done on the efficiency of laboratories, which requires more attention. [ABSTRACT FROM AUTHOR]

The research delt with the effect of labour out-migration on output per hectare and efficiency of wheat and teff producers in Kembata-Tembaro and Hadiya zones of Ethiopia based on primary data gathered from 415 random sample of rural households. The multinomial endogenous switching model was used as an analytical model. According to the stochastic frontier model, the mean efficiency of wheat and teff are 82.98 and 66.43 per cent, respectively. According to the econometric results, rural–urban and international migration reduces wheat productivity by 110.94 and 179.11 kg, respectively. The average treatment effect on treated (ATT) also revealed that participation in international migration reduces Teff producers' technical efficiency by 5.51 per cent. However, teff productivity is reduced by 382.94 and 747.49 kg due to rural urban and international migration, respectively. The lost labour channel of the modern theory of migration is maintained by the result of the study. So as to minimise the negative impact of out-migration in the study area, policymakers must focus more on promoting access to credit, irrigation, land, off-farm employment and public services for rural households. [ABSTRACT FROM AUTHOR]

AbstractMultinational firms establish foreign affiliates to reduce production and transaction costs and open markets. This study was conducted to determine whether foreign affiliates are efficient in production—the efficiency of foreign affiliates established by Korean multinationals through foreign direct investment from 2007 to 2018. DEA efficiency was measured by dividing it into pure, technical, and scale efficiency. An empirical analysis using the panel Tobit and Probit models examined the factors affecting efficiency decisions. It was confirmed that the total number of foreign affiliates’ employees significantly affects their efficiency. In addition, it was analyzed that establishments with traditional FDI motives, such as taking advantage of low wages and promoting exports, harm the efficiency of foreign affiliates. [ABSTRACT FROM AUTHOR]

This work assesses the technical efficiency (TE) in agricultural production under irrigation of corn, alfalfa, sorghum, and plantain; the analysis is conducted for three hydrological subregions of Mexico: Río San Juan (north), Valley of Mexico (center) and Valle Bajo de Grijalva (South). The measurement was carried out by agricultural cycle (spring-summer, autumn-winter and perennial), and by land size. We use stochastic frontier analysis to corroborate whether the farmer’s skills favor efficiency, with a production function that relates irrigated land as a basic element, and a set of explanatory socioeconomic variables. Despite limitations in the data, the results contribute to the knowledge of TE in Mexican agriculture. Indirectly, the contribution of irrigation is recognized, so identifying their economic relevance could help define strategies to improve agricultural production and support water management in agriculture. [ABSTRACT FROM AUTHOR]

Clean production of electricity is not only cost-effective but also effective in reducing pollutants. Toward this end, the use of clean fuels is strongly recommended by environmentalists. Benchmarking techniques, especially data envelopment analysis, are an appropriate tool for measuring the relative efficiency of firms with environmental pollutants. In classic data envelopment analysis models, decision-makers are faced with production processes in which reducible inputs are used to produce expandable outputs. In this contribution, we consider production processes when the input and output data are given in stochastic form and some throughputs are reducible and some others are expandable. A stochastic directional distance function model is proposed to calculate the relative technical efficiency of firms. In order to evaluate firm-specific technical efficiency, we apply bootstrap DEA. We first calculate the technical efficiency scores of firms using the classic DEA model. Then, the double bootstrap DEA model is applied to determine the impact of explanatory variables on firm efficiency. To demonstrate the applicability of the procedure, we present an empirical application wherein we employ power plants. [ABSTRACT FROM AUTHOR]

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Given the complex managerial tasks and the risks and uncertainties involved in agricultural production, it is expected that personality traits may play an integral role in shaping farmers' performance. This study uses a large rural household survey dataset collected in three rice-producing provinces in China to examine this proposition. We find that openness to experience and internal locus of control have favourable effects on technical efficiency (TE), while agreeableness and neuroticism are associated with lower TE. Cognitive skills, as measured by years of education, do not contribute to higher TE of the interviewed farmers. These results imply that the motivational component of human capital (i.e. personality traits) is of greater importance for a farmer's managerial performance than cognitive skills attained through current formal education. The effectiveness of policies aimed at improving rural welfare may be enhanced by adapting agricultural training programmes to include fostering entrepreneurial and social skills, especially for those with unfavourable personality traits for agricultural production, in addition to improving agricultural knowledge. [ABSTRACT FROM AUTHOR]

This study focuses on evaluating the technical and scale efficiencies of smallholder pineapple farmers in Ghana's Central Region. We surveyed 320 participants selected using random sampling and applied an input-oriented Data Envelopment Analysis (DEA) method to gauge their technical, pure, and scale efficiencies. Our findings indicate that the mean technical efficiency among these farmers is 0.505, with individual scores ranging from 0.079 to 1.000. Notably, 90.82% of the farmers are operating below maximum efficiency levels, suggesting a potential input reduction of up to 49.5% while maintaining current production levels. Relaxing the assumption of constant returns under Variable Returns to Scale (VRS) conditions reveals a notable improvement in technical efficiency, with 10.82% more farmers achieving optimal efficiency levels. Furthermore, our analysis highlights scale inefficiencies, with 67.26% of farmers operating below optimal scale levels. By increasing production by 22.8%, these scale-inefficient farmers could enhance their efficiency and productivity within existing technological frameworks. These findings underscore the importance of collaborative efforts among policymakers, practitioners, and stakeholders within the agricultural value chain to implement interventions such as improving access to technology and innovation for smallholder farmers and making necessary investments in farmer education and training programs to enhance both technical and scale efficiencies in Ghana's pineapple sector. Such initiatives can drive sustainable growth, improve farmers' livelihoods, and bolster the sector's overall competitiveness. [ABSTRACT FROM AUTHOR]

This study applies data envelopment analysis (DEA) to gauge technical efficiency and allocative efficiency in China's beef cattle-fattening industry using survey data. The Tobit model considers the salient determinants that drive these efficiencies. The results indicate that (1) large-scale farms exhibit robust TE and pure technical efficiencies (PTE), whereas scale efficiencies (SE) diverge significantly between large and medium-sized operations. The cost efficiency (CE) of smaller farms lags behind their larger counterparts, with the latter displaying greater revenue efficiencies (RE) and profit efficiency (PE). (2) The influence of identical factors on the efficiency of beef cattle fattening production can vary, sometimes antithetically, across different scales. Local policy interventions must be differentiated according to farm type and size. (3) The unique context of China's national conditions and the status quo of livestock farming render the dual implementation of environmental regulations and technological subsidies less viable for Chinese beef cattle farms. These entities should prioritize production over technological innovation and advancement. Policymakers should adopt strategies such as targeted skill/technological training for farm managers at particular scales of operation. This could represent a critical trajectory to augment the efficiency of beef cattle production and increase beef yield in China. [ABSTRACT FROM AUTHOR]

The Business Roundtable's "Purpose of a Corporation" letter announced a shift from stockholder primacy to stakeholder primacy. Interestingly, we contend the letter's language employed a technical efficiency emphasis, suggesting a firm's executives chose to make this shift because they believed doing so would improve the firm's financial performance, via improved corporate governance. We examine whether investors actually accepted the technical efficiency arguments at face value, or in contrast believed the announcements were merely a "rational myth," what management thought investors would want to hear. We employ a 2‐day cumulative abnormal return (CAR) event study for 140 publicly‐held firms. Overall, we find investor support for the announcement. In addition, we found how returns to firms with prior similar announcements were negative at the time of the announcement. Also, the returns for firms having multiple signatories were positive and significant. [ABSTRACT FROM AUTHOR]

The efficiency of poultry production plays a crucial role in ensuring food security and maintaining human health sustainability. Although extensive research has been done on the largest poultry-producing countries, the European Union's contribution has not been thoroughly investigated, especially in Central and Eastern Europe. This study aims to fill this gap by analysing the technical efficiency of poultry farms in Hungary and Poland. We use the stochastic metafrontier approach to Farm Accountancy Data Network (FADN) data from 2010 to 2015. The results suggest that both countries have technical inefficiencies. The meta technical efficiency (MTE) was higher in Poland than in Hungary, driven by both a higher technology gap ratio (TGR) and higher (country-specific) technical efficiency (TE) in Poland. In both countries, returns to scale were increasing, which suggests that policies that increase scale of operation could increase efficiency. Furthermore, the study highlights the importance of technological gaps for several farms both in Poland and Hungary; therefore, policies should also focus on supporting investments in technology adoption and innovation. This could involve providing subsidies or grants for the adoption of advanced farming technologies, such as automated feeding systems or data analytics for optimizing production processes.

Abstract Background Priority-setting becomes more difficult for decision-makers when the demand for health services and health care resources rises. Despite the fact that the Ethiopian healthcare system places a strong focus on the efficient utilization and allocation of health care resources, studies of efficiency in healthcare facilities have been very limited. Hence, the study aimed to evaluate efficiency and its determinants in public health centers. Methods A cross-sectional study was conducted in the East Wollega zone, Oromia Regional State, Ethiopia. Ethiopian fiscal year of 2021–2022 data was collected from August 01–30, 2022 and 34 health centers (decision-making units) were included in the analysis. Data envelope analysis was used to analyze the technical efficiency. A Tobit regression model was used to identify determinants of efficiency, declaring the statistical significance level at P

Abstract Background Medical diagnostic laboratories are an essential work environment that plays an important role in diagnosing, treating, and being sensitive to diseases. One way to evaluate laboratories’ performance is to calculate their efficiency. This study investigates the efficiency of laboratories that are related to health centers in the south of Iran. Methods This study was conducted in 2021. The input numbers include: the number of technical personnel and the number of cell counters, and the output data includes: the scores obtained from the level 2 health laboratory evaluation list. And efficiency was calculated with DEAP software. The analysis is accomplished by the assumption of input-oriented. Findings The efficiency of laboratories of Orzueeyeh and Ravar Cities had the highest efficiency with the assumption of variable returns to scale efficiency 1, and the model of all laboratories is the laboratory of Ravar City. The laboratories of Kuhbanan and Rabor cities had the lowest efficiency with the assumption of variable returns to scale efficiency of 0.859 and 0.899, respectively. The average scale efficiency, Variable returns to scale, and constant returns to scale for laboratories in the cities of Kerman province are 0.842, 0.943, and 0.895, respectively. Conclusions To increase the efficiency of laboratories, significant resources and funds should be used, as well as few studies have been done on the efficiency of laboratories, which requires more attention.

Abstract Background When considering new technologies that are not widely known such as agricultural smartphone apps, exposure plays a significant role in facilitating farmers’ decision to use the agricultural smartphone apps. In this study, we examine the role of exposure to agricultural smartphone apps on adoption of agricultural smartphone apps among smallholder farmers in Southwest, Nigeria and also evaluates the effect of use of agricultural smartphone apps on total factor productivity and technical efficiency of farmers. Through counterfactual framework evaluation approach, we used a multistage sampling procedure to select 380 farmers in Southwest, Nigeria through well-structure questionnaire. Results We found that the agricultural smartphone apps user rate in 2022 for the sub-sample of the exposed farmers was higher in both Oyo and Osun State, indicating that exposure to agricultural smartphone apps played an important and significant role in increasing the adoption and use of agricultural smartphone apps in Nigeria. We also found that the mean TFPI and TE of the treated (users of agricultural smartphone apps) is higher than the non-treated and control group (non-users) implying that the users of agricultural smartphone apps have higher productivity margin than the non-users. Conclusion Based on the result of the study, it was concluded that exposure to the technology has a higher chances of increasing the use of agricultural smartphone apps across farmers populations in Southwest, Nigeria.

This study analyzes the economic efficiency of soybean production under contract and noncontract farming systems in the Northern region of Ghana. Using survey data from 374 soybean farmers, comprised of 200 contract farmers and 174 non-contract farmers, a stochastic frontier analysis and fractional regression models were employed to estimate technical, allocative, and economic efficiencies. The results reveal that contract farmers had a mean technical efficiency of 0.92, allocative efficiency of 0.869, and economic efficiency of 0.943, while non-contract farmers had mean technical efficiency of 0.973, allocative efficiency of 0.734, and economic efficiency of 0.866. Positive determinants of efficiency included education, farming experience, access to extension services, and participation in soybean contract farming. Off-farm activities and crop diversification negatively impacted efficiency. Contract farmers exhibited increasing returns to scale, while decreasing returns to scale prevailed among non-contract farmers. Factors influencing soybean output and production costs were also analyzed. The study highlights opportunities for enhancing soybean productivity and reducing production costs through improved resource allocation, adoption of training and extension services, and promoting contract farming arrangements that provide access to inputs, credit and technical support.

Smallholder oil palm farming is the main livelihood in Batanghari District, although its productivity has not shown maximum results. Maximum productivity achieved, it is necessary for farmers to do their business efficiently. This study aims to analyze technical efficiency and socio-economic factors that affect the technical efficiency of smallholder oil palm farming in Batanghari District. The research sample was determined using the multistage sampling method, which was used to sample farmers using simple random sampling. The number of respondents was 100 farmers. The stochastic frontier production function was used for data analysis. The results showed that the average technical efficiency of oil palm farming was 0,89 and had reached efficiency. However, this level can still be increased by 0,11 to achieve the highest level of technical efficiency. The technical efficiency of farming is affected by socio-economic factors, namely farming experience, distance from home to the farm, and the existence of partnerships. Based on the study's results, the technical efficiency of oil palm cultivation can be improved by utilizing production parameters precisely and accurately and increasing farmers' resources to achieve maximum production. For sustainable agricultural development, further research is needed to analyze the economic efficiency of oil palm farming so that the overall picture of both technical and economic efficiency can be seen.

Potatoes are among the vegetables highly susceptible to climate change, and its consequences can significantly affect technical efficiency.However, the production of potato relatively fluctuated due to some factors influencing it. The study aims to analyze the factors affecting potato production, measure the level of technical efficiency in potato farming, and identify the socio-economic factors that influence technical inefficiency in potato farming, both in the rainy and dry seasons. The study was conducted in Merangin Regency, Jambi Province. A purposive sampling method was used to select the research area and collect data from 102 potato farmers. The data were analyzed using the Stochastic Frontier Cobb-Douglas production function model with a maximum likelihood estimation (MLE) approach. The research results show that land and seed variables significantly influence potato production, both in the rainy and dry seasons. Meanwhile, fertilizer P and labor only significantly influence the dry season. The average level of technical efficiency in the dry season (0.89) is higher than in the rainy season (0.73). The results of the average difference test (t-test) show that in the dry season, the level of technical efficiency has a higher value than in the rainy season, with a significance of 1%. The significant socio-economic variables influencing technical efficiency are membership in farmer groups.

This research focuses on analyzing the effect of high employment temporality on technical efficiency and productivity. Previous literature points out a set of benefits and drawbacks related to fixed-term contracts. To ascertain the influence of temporality on efficiency, the critical case of the hotel sector in the Canary Islands is studied where the temporary employment rate (40%). So this paper explores the effect of temporary employment on technical efficiency in the hotel sector of the Canary Islands (a Spanish region). The magnitude of this case study can be clearly checked, given that the Canary Islands is the most popular region in the European Union visited by residents. A production stochastic frontier is estimated by distinguishing between two types of employment: permanent and temporary. Results suggest that high levels of temporality tend to reduce technical efficiency and productivity. A high conversion rate from temporary to permanent jobs seems to increase efficiency. The contribution of this paper is threefold: (i) filling the gap in the literature on the influence of temporary employment on technical efficiency, evaluating its effect for a case study where job temporality is dramatically high, (ii) partial factor productivities for permanent and fixed-term workers are estimated, and (iii) exploring the influence of less studied variables like the level of conversion from fixed-term to permanent employment on efficiency. The findings can be relevant for human resources management for firms where temporary rates are high. Human resource management should consider the type of labor contracts used, as well as the perspectives of conversion into permanent ones for their temporary workers, given their potential influence in technical efficiency, labour productivity, and firm performance.

AbstractIn this research, the spatial efficiency coefficient of Business incubator of Iran's technology units has been analyzed for thirty provinces. For this purpose, by using data envelopment analysis method and the variable return model to the cluster-based scale, the values of technical, scale and managerial efficiency have been perused. The results show that there is no positive and significant relationship between academic rank and technical efficiency of Business incubator. 12 provinces have lower than average technical efficiency, which Kerman province has the lowest technical efficiency value of 0.315, despite being ranked 21-30 and located in a semi-industrial region. It would be said that effective interaction between universities and industries accelerates innovation, Therefore, the absence of an innovative environment, the relationship between the formal management mechanisms of the university and industry, and the low managerial efficiency (0.382), moderates the academic innovation functions and causes a weak connection between these two areas. On the other hand, despite the fact that Bushehr province is at the level of 41-50 in the university ranking and in a weak industrial area, the technical efficiency (number 0.931) is higher than the average, which is mostly due to the high management efficiency. The results of the scale efficiency study show that Khuzestan, Kurdistan and Markazi provinces have increasing efficiency compared to the scale. It would be said that these provinces, due to the feature of increasing efficiency, if using a larger scale, enjoy a lower average cost level and as a result increase the output efficiency. Also, 30 percent of the surveyed provinces are in the stage of decreasing efficiency compared to the scale, and this means that they benefit from less production (compared to the increase in inputs).Thus, using more inputs and less production means reducing technical efficiency. Also, based on the obtained results, 18 centers also have a constant return to scale, which indicates that if these units increase all their production factors, the amount of production will increase by the same amount and the change in production scale does not affect their technical efficiency.IntroductionIn today's world, besides their educational goals, universities are assigned to participate more in the processes of innovation and technology development, which is possible through engaging in entrepreneurial activities. To promote entrepreneurial activities, policy makers are looking for a mechanism to commercialize research findings in universities. Commercialization of academic research achievements and technology development is known as the foundation of progress and continuation of economic growth. Since knowledge is developed and accumulated in universities with a dense density, therefore universities can be recognized as an important tool in facilitating the formation of a knowledge-based economy and speeding up regional economic and social development. For this reason, many countries are pursuing university reforms with the approach of decentralization and acting more competitively, increasing the commercialization of research results and performance-based budgets. Nowadays, according to the advancement of technology and the change in the nature of universities, their evolution can be described as follows: first generation universities have emerged with educational purposes only, second generation universities with research or industrial purposes, and finally Third generation universities are moving towards creating entrepreneurial universities. The third generation of universities includes the three steps of education, research and technology. Transferring technology from the university to the private sector requires the use of market knowledge. Accordingly, as entrepreneurial universities, by producing and distributing knowledge, universities play an essential role in the development of technology, innovation in the industry, and the formation of spin out companies. The importance of spin off companies is revealed when university education increases and then commercialization becomes possible through the transfer of universities to industry. In today's world, considering the dynamic economy, constant attention to entrepreneurship and technology transfer is an important principle. The increasing the number of university graduates and the increasing attention to university entrepreneurship is an important factor for the expansion of spin off companies. Academic spin off companies are companies that have been established to exploit the technical knowledge created in universities and have attracted the attention of researchers and policymakers due to their ability to create wealth and advance scientific knowledge. The "Bayh-Dol" law was passed in 1980 with the aim of encouraging universities to participate in the commercialization process, and in this way, it made universities eager to produce and transfer technology between industries and earn money. By promulgating this law, universities continuously support start-up companies for the commercialization of ideas. The commercialization of ideas by start-up companies is much easier than old businesses.If the formation of reproductive companies is institutionalized in universities, in addition to providing entrepreneurial opportunities, the legal rights of universities in relation to their intellectual property will also be restored. Also, while providing a suitable platform for research and development opportunities for universities, a new source of income is also created for the universities. The main purpose of creating spin off companies should be sought in the transformation of science into wealth. In other words, the essence of creating spin out companies is commercialization, and commercialization is the executive solution of turning science into wealth.This paper is organized as follows: Section 2 briefly presents the theoretical framework. Section 3 presents the research methodology. Section 4 introduces the data used in the research. In section 5, it discusses the findings of the estimates, and section 6 concludes in two sub-sections, a summary of the findings and policy suggestions are presented.Research methodologyData Envelopment Analysis (DEA) method is used in this article. DEA is a method based on linear programming which the manager can use the best decision-making unit (DMU) as a model for other units. Data envelopment analysis is a method that, in addition to measuring efficiency, suggests ways to improve it using the ratio of output to data for each individual level and how to increase productivity at all levels. One of the issues of comprehensive data analysis is the ranking of efficient companies, in which the units are classified as efficient and inefficient. DEA models introduce the efficiency of units that are known to be inefficient. Data envelopment analysis is a non-parametric method based on mathematical programming, which is used to evaluate the relative efficiency of decision-making units with several inputs and outputs. In this study, efficiency values have been estimated by using the data envelopment analysis method and variable return to scale (VRS) model.Research data In this study, in order to measure the technical efficiency, scale and management of business incubator in 30 provinces of the country, the data envelopment analysis approach has been used.Finding and SuggestionIn this research, the efficiency of commercialization of the growing companies of Iran's technology units in business incubator for thirty provinces has been analyzed. The results obtained from the estimation of the model show that the provinces that do not have unit efficiency during the years under review can, on average, increase the output by 14.5% without using more resources and with proper management, as well as through improvement in scale can increase the output by 3.4%. Based on this, the following policy proposals are presented:1- Due to the lack of an endogenous and uniform structure in terms of industrial and academic structure in the provinces of Iran and the diversity of regional talents, the design of the development model of business incubators should be diverse and different, and a homogeneous model for regional development cannot be used.2- In competitive markets, the ability to commercialize products is essential for the survival of companies, so companies must be continuously innovative in order to respond to the challenges that exist in the industry. And by being aware of the factors affecting the commercialization process, they seek to create innovation, gain competitive advantage and increase market share, and commercialize their products.3- Wider communication between university and industry through communication channels such as: implementation of joint research projects, consulting and training, holding conferences and establishing informal communication between industry and university researchers.

Abstract Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries’ technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector’s potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector.

Abstract This study seeks to determine the impact of agricultural subsidies on the efficiency of Algerian farms. To do so, we estimated a Stochastic Frontier Analysis (SFA) for Algerian data covering the period from1970 to 2020. Two variables were used to describe the agricultural subsidy: the first is total agricultural support, and the second is a dummy variable that takes the values 0 and 1 to express the coupling of subsidies to production. The variable of support for agriculture production and producers takes the value of one (1) in the era when the support is not related to production (decoupled support). It takes the value zero (0) when there is explicit support for production and producers (coupled support).The findings revealed that total subsidies had a negative impact and statistically significant on the technical efficiency of Algerian farms. While, the decoupling has a positive effect on efficiency (negative on inefficiency), but without significance.

Abstract Under the influence of market rules, state intervention in development process is obviously necessary, especially in the context of emerging countries with an incomplete and non-mordern market economy toward the global race of sustainability. Applying 2590 enterprises covering 63 provinces and cities in the General Statistics Office, this study aims to evaluate the influence of state on the technical efficiency of enterprises. A fractional regression analysis model is employed purposefully since the technical efficiency of the dependent variable is an estimated randomly variable. The research findings unequivocally indicate a substantial influence of the state on the technical efficiency of livestock product processing companies. Moreover, when studying each specific aspect in isolation to gauge the role of the state, a discernible negative impact is evident on the technical efficiency of these enterprises. Consequently, this study implies that for tangilbe improvements in the technical efficiency of enterprises, the state should adopt a comprehensive approach, simultaneously implementing all aspects that demonstrate its role in the sector. By adopting such a holistic strategy, the state can create a more conducive environment toward development sustainability for improving the technical efficiency of livestock product processing enterprises.

Abstract In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.

Abstract Background Onions are economically and nutritionally important vegetable crops. Despite advances in technology and acreage, Indian onion growers face challenges in realizing their full productivity potential. This study examines the technical efficiency of onion growers, the factors influencing it, and the constraints faced by those adopting drip irrigation in the Ghod river basin of western Maharashtra. A sample of 480 farmers including those practicing drip irrigation and those not practicing it, was selected from Junnar, Shirur, Parner, and Shrigonda blocks of the basin. The primary data was collected through semi-structured interviews. Analytical tools such as the Cobb-Douglas production function (represents technological relationship between multiple inputs and the resulting output), a single-stage stochastic frontier model, the Tobit model, and descriptive statistics were used to assess the technical efficiency of onion production at the farm level. Results According to the maximum likelihood estimates of the stochastic frontier analysis, drip adopters exhibited a mean technical efficiency of 92%, while for non-adopters it was 65%. It indicates that the use of drip irrigation technology is associated with higher technical efficiency. The association of technical efficiency and socio-economic characters of households showed that education, extension contacts, social participation, and use of information sources had a positive influence on technical efficiency, while family size had a negative influence on the drip irrigation adopters. For non-drip adopters, significant positive effects were observed for landholding, extension contact, and information source use. The major constraints faced by drip system adopters included a lack of knowledge about the proper operating techniques for drip systems and the cost of maintenance. Conclusion The differences with inputs associated with two irrigation methods showed that the response of inputs to increase onion yield is greater for farmers who use drip irrigation than for farmers who do not, and are a result of the large differences in the technical efficiencies. These inefficiencies and other limitations following the introduction of drip irrigation, such as lack of knowledge about the proper operations, need to be addressed through tailored training for farmers and further interventions.

Digital technology plays a crucial role in advancing sustainable farming and ensuring food security, especially in developing countries. This study evaluates the impact of Internet technology usage on technical efficiency in crop productivity, using data from 600 wheat farmers in rural Pakistan. It addresses the imperative need to enhance agricultural practices within the context of sustainable food production. To achieve this, a matched sample of Internet users and non-users was formed through propensity score matching. The study employs the stochastic frontier method with sample selection adjustment, ensuring a robust evaluation of technical efficiency between these groups. The findings reveal a positive influence of Internet usage on efficiency, persisting even after mitigating self-selection bias from observed and unobserved factors. Internet users exhibit a technical efficiency score of 0.62, surpassing the 0.55 score of non-users. Quantile regression analysis exposes varying impacts of Internet usage on technical efficiency, with less efficient farmers experiencing substantial improvements. Widespread Internet adoption holds the potential to significantly enhance agricultural production for growers. The research underscores the role of promoting Internet utilization to stimulate growth and improve farming efficiency within the evolving digital economy. Policymakers are advised to promote the adoption of modern technology to enhance crop production and support economic growth. [ABSTRACT FROM AUTHOR]

Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries' technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector's potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess the technical efficiency of the use of investment resources allocated to municipalities in Cameroon. The data used come from the Special Inter-municipal Equipment and Intervention Fund (FEICOM), the National Participatory Development Programme (PNDP) and the Public Investment Budget (BIP), for the period 2010 to 2020, and the Data Envelopment Analysis (DEA) method. The results shows that the BIP counter has the highest efficiency score, at 1 for the whole period, while the scores of the FEICOM and PNDP windows are 0.896 and 0.857 respectively. Secondly, the pooling of resources from the different windows increases the efficiency score obtained, an average of 0.96 for the whole period, even if the new scores remain lower than those of BIP. These results, which highlight the good performance of the BIP window, justified by the significant learning effects from which this window benefits. [ABSTRACT FROM AUTHOR]

This study is devoted to the analysis of the statistical relationship between the efficiency of an insurance company and a number of factors characterizing the structures of its assets. Efficiency in the study is considered as a metric that evaluates the quality of an organization's management, which is the one of the most important characteristic of its financial stability. The empirical analysis was carried out using data from the financial statements of insurance companies for the period from 2017 to 2020 of the group of leaders in terms of insurance premiums of the Expert RA rating agency based on the results of 2020. Life insurance companies, reinsurance companies and mutual insurance companies were excluded from this list due to the specifics of their business and financial statements. For the companies included in the final sample, an assessment of overall efficiency was built. The methodology of its calculation is formulated and developed in [3, 14, 15]. It is based on Data Envelopment Analysis (DEA). The partial efficiency indicators obtained for a certain set of DEA model specifications are aggregated into several indicators using the principal component analysis method (PCA). It is important that there is a positive correlation between the overall efficiency indicator and the partial efficiency indicators. The first principal component acts as an indicator of overall efficiency, the others allow one to identify its sources. This makes it possible to compare companies that have the same overall efficiency. Further, for all representatives of the final sample, a regression model of the statistical relationship of overall efficiency with the characteristics of the asset structure was built. The model specification was performed based on the MFP (Multivariable Model-Building with Fractional Polynomials) algorithm [16, 17], which allows to adapt the specification of the regression model to the properties of the data and identify nonlinear statistical relationships. The results of the evaluation of the model allow us to assert that the general and, accordingly, all partial performance indicators have a statistical relationship with the selected characteristics of the asset structure. The nature of the relationship is predominantly nonlinear. The results obtained in the work can be useful in forming a strategy for managing the financial stability of an insurance company, as well as for potential partners and investors in solving the task of benchmarking. [ABSTRACT FROM AUTHOR]

The study used a cross-county survey from Kenya to investigate smallholder tea farmers' performance using a stochastic metafrontier framework. According to the results, farmers in all four regions are falling short of their potential with the mean technical efficiency ranging from 0.69, 0.77, 0.61, and 0.74, respectively, for the Nandi, Mau, Kisii, and Kericho regions. Comparing its performance with the technology available in the industry, each region faces a technology gap. Even though some variables were not statistically significant, a combination of socioeconomic and farm-specific factors were identified as sources of technical inefficiency among farmers. The farmers in all regions, however, possess the potential to overcome technological constraints and achieve higher levels of productivity. Kenya Tea Development Agency Ltd should, therefore, enhance its efforts to help the farmers improve their management and technical skills on how to use their resources more efficiently. [ABSTRACT FROM AUTHOR]

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Financial inclusion paves the path towards inclusive growth. The Government of India launched the Pradhan Mantri Jan-Dhan Yojana (PMJDY) in 2014 with a similar aim. The present study measures efficiency of 25 banks using the data envelopment analysis to ascertain how the banks have functioned under the PMJDY scheme. The study has been conducted for a duration of 7 years beginning from the year the scheme was introduced in 2014–2015 till 2020–2021. Results of the empirical analysis have indicated that the performance of public sector banks has been better than the private banks in expanding financial inclusion under the PMJDY programme. Additionally, measurement of projection and shortfall of the outputs of banks has shown that very few banks have performed efficiently in furthering the objectives of PMJDY scheme. Thus, the overall evidences derived from the analysis suggest that the inefficient banks need to expand their banking services for the deprived. Regular assessment of efficiency would assist in identifying and thereby implementing necessary steps to overcome the obstacles in achieving the financial inclusion goals. This would also improve the efficiency level of the banks having low-efficiency scores. Moreover, banks have a social responsibility to properly implement the schemes initiated by the government. [ABSTRACT FROM AUTHOR]

Efficiency analysis is crucial in healthcare to optimise resource allocation and enhance patient outcomes. However, the prompt adaptation of inputs can be hindered by adjustment costs, which impact Long-Run Technical Efficiency (LRTE). To bridge this gap in healthcare literature, this research employs a Bayesian Dynamic Stochastic Frontier Model to estimate parameters and explore healthcare efficiency dynamics over time. The study reveals the LRTE for New Zealand District Health Boards (DHBs) as 0.76, indicating around 32% more input utilisation due to adjustment costs. Most DHBs exhibit consistent short-run operational efficiency, with the national Short-Run Technical Efficiency (SRTE) very close to the LRTE. Among the tertiary providers, Auckland and Capital & Coast DHBs operate below the LRTE level, setting them apart from other tertiary providers. Similarly, Tairawhiti and West Coast DHBs also fall below the LRTE level, as indicated by their SRTE scores, potentially influenced by their unique healthcare settings and resource challenges. This research brings a new perspective to policy discussions by incorporating the temporal dynamics of decision-making and considering adjustment costs. It underscores the need to balance short-term and long-term technical efficiency, underlining their collective significance in fostering a sustainable and efficient healthcare system in New Zealand. [ABSTRACT FROM AUTHOR]

Promoting the productivity and environmental sustainability of aquaculture is critical in ensuring its healthy development. This study assesses freshwater aquaculture's technical efficiency and ecological efficiency in China's 19 inland provinces from 2008 to 2019, aiming to reveal its productivity and environmental sustainability status. We employ the three‐stage Data Envelopment Analysis‐CCR (T‐DEA‐CCR) and three‐stage Slack‐Based Measure‐DEA (T‐SBM‐DEA) methods to explore the technical efficiency and the ecological efficiency while accounting for environmental conditions and random errors. The average technical efficiency and ecological efficiency during 2008–2019 are 0.857 and 0.702, respectively, indicating substantial scope for enhancing the productivity and environmental sustainability of China's inland aquaculture. We further investigate the regional development using the club convergence, finding that the provincial‐level technical efficiencies have already achieved population convergence while the ecological efficiencies diverge into two clubs, suggesting that Chinese freshwater aquaculture's productivity and environmental sustainability have different development pathways. Acknowledging the pivotal roles of environmental protection and growers' training in aquaculture's productivity and environmental sustainability, policymakers may institute funding and recognition to foster the adoption of innovative, environmentally responsible practices by operators. [ABSTRACT FROM AUTHOR]

Summary: We propose a flexible stochastic production frontier model with fixed effects for the panel data in which the semiparametric frontier is additive with bivariate interactions. To avoid potential misspecification and/or "wrong skew problem" due to distributional assumptions, we model the conditional mean of the inefficiency to depend on environmental variables and to be known up to a vector of parameters. We propose a difference‐based estimator for parameters characterizing the conditional mean of the inefficiency term, a profile series estimator, and a kernel‐based one‐step backfitting estimator for the frontier to facilitate inference. We establish their asymptotic properties and show that each component in the frontier estimated by the kernel‐based backfitting has the same asymptotic distribution as the one estimated with the true knowledge on the other components in the frontier (i.e., the oracle property). Through a Monte Carlo study, we demonstrate that the proposed estimators perform well in finite samples. Utilizing a panel of Chinese firm‐level data in 2000–2006, we apply our method to estimate the frontier and efficiency scores and conclude that export plays a significant role in reducing the efficiency of firms. [ABSTRACT FROM AUTHOR]

In this research, the spatial efficiency coefficient of Business incubator of Iran's technology units has been analyzed for thirty provinces. For this purpose, by using data envelopment analysis method and the variable return model to the cluster-based scale, the values of technical, scale and managerial efficiency have been perused. The results show that there is no positive and significant relationship between academic rank and technical efficiency of Business incubator. 12 provinces have lower than average technical efficiency, which Kerman province has the lowest technical efficiency value of 0.315, despite being ranked 21-30 and located in a semi-industrial region. It would be said that effective interaction between universities and industries accelerates innovation, Therefore, the absence of an innovative environment, the relationship between the formal management mechanisms of the university and industry, and the low managerial efficiency (0.382), moderates the academic innovation functions and causes a weak connection between these two areas. On the other hand, despite the fact that Bushehr province is at the level of 41-50 in the university ranking and in a weak industrial area, the technical efficiency (number 0.931) is higher than the average, which is mostly due to the high management efficiency. The results of the scale efficiency study show that Khuzestan, Kurdistan and Markazi provinces have increasing efficiency compared to the scale. It would be said that these provinces, due to the feature of increasing efficiency, if using a larger scale, enjoy a lower average cost level and as a result increase the output efficiency. Also, 30 percent of the surveyed provinces are in the stage of decreasing efficiency compared to the scale, and this means that they benefit from less production (compared to the increase in inputs).Thus, using more inputs and less production means reducing technical efficiency. Also, based on the obtained results, 18 centers also have a constant return to scale, which indicates that if these units increase all their production factors, the amount of production will increase by the same amount and the change in production scale does not affect their technical efficiency. [ABSTRACT FROM AUTHOR]

Objectives of our study are to develop a procedure for intertemporal comparison of both technical and cost efficiency and estimate farm efficiency for the Korean rice industry from 2003 to 2017. The newly developed base‐year procedure excludes frontier shift and price effects from the standard procedure for intertemporal comparison. An adjusted central limit theorem for sample T‐tests is applied to avoid potential bias from efficiency scores by the Data Envelope Analysis. Our empirical results show that the two procedures yield different scores and trends. The standard approach indicates declining efficiency, while the base‐year method shows overall improvement in farm efficiency. [ABSTRACT FROM AUTHOR]