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This study investigates the existence of solutions for the key plant capacity utilisation (PCU) concepts using general nonparametric technologies. This is done via a theoretical review of existing and some new PCU concepts. Focusing on short-run and long-run output-oriented, attainable output-oriented, and input-oriented PCU notions, we first investigate the existence of solutions at the firm level. Under mild axioms, this question regarding the existence of solutions for these PCU concepts at the firm level is affirmatively answered under variable and constant returns to scale as well as under convex and nonconvex assumptions. However, short-run and long-run output-oriented and attainable output-oriented PCU concepts may not be implementable depending on certain conditions. There are no such reservations for the input-oriented PCU. Then, for this same range of PCU concepts, we explore the more difficult question as to the existence of solutions at the industry level. The output-oriented and attainable output-oriented PCU exist at the industry level under strict conditions: existence and attainability are interwoven at this level. The industry input-oriented PCU is always feasible at the industry model. This theoretical review is supplemented by a semi-systematic empirical review, and an empirical application. We conclude that input-oriented PCU is clearly the best concept. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to initiate new avenues of research by examining optimal intellectual capital (IC) inputs, introducing three theories into the discussion: diminishing returns to scale, transaction costs economics and efficiency wage theory. In the second part, it advocates for demonstrating the existence of such non-optimality through empirical tests. Design/methodology/approach: This paper is divided into two parts. The first part provides a theoretical justification for the necessity of observing nonlinear relationships between IC inputs and firm performance. In the empirical section, the research design follows a four-step process, each progressively building on insights gained from the preceding phase: (1) establishing a baseline linear regression model; (2) introducing the logarithm of the IC inputs; (3) incorporating the square terms of the IC inputs and (4) investigating the phenomena of over- and under-input in IC. Findings: The background theories and the obtained results highlight the necessity for firms to adopt a strategic approach to IC, acknowledging the diverse effects of IC components on different outcomes. They emphasize the nonlinear nature of IC returns, underscoring the importance of investing up to an optimal level to maximize benefits. Practical implications: The study's discovery of optimal levels for the components of IC highlights the importance for practitioners to identify and invest up to these optimal levels. This ensures that IC initiatives are strategically aligned to maximize their positive impact on firm performance. Originality/value: The integration of theories such as diminishing returns to scale, transaction costs economics and efficiency wage theory, alongside traditional frameworks like the resource-based view, the theory of dynamic capabilities and the knowledge-based theory of the firm, opens up new avenues for research on IC. The proposed methodology and measures – from financial reports – provide opportunities for replicating this type of study. [ABSTRACT FROM AUTHOR]

We present a footloose capital model in a two‐country economy and the manufacturing and natural resource sectors with heterogeneous manufacturing firms to analyze the impacts of trade liberalization and technological progress on the net capital flows, net export, and social welfare. Our main analytical result is that a lagged country initially experiences capital outflow due to the high technological gap in the manufacturing sector with increasing returns to scale, then capital inflow due to the home market effect. This corresponds with the fact that China was a net importer of manufactured goods initially, and became a net exporter recently. These results are consistent with the data obtained after the reform and opening‐up policy in 1978. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to review the relationship between per capita income and aggregate emission in an economy populated by rational agents. According to the environmental Kuznets curve (EKC) hypothesis, pollution–income relationship is an inverted U-shaped curve. This paper aims to derive that relationship in an endogenous way and extends the relevant literature in an important way. Design/methodology/approach: This paper formulated a general equilibrium model of homogenous population with identical tastes and preferences. Production side is modelled with firms operating in a monopolistically competitive environment. The approach is modelling the economy in an analytical way so that closed form solutions can be achieved. Model simulations have also been performed to get a clear view of results. Findings: This study shows that increasing returns to scale in abatement technology ceases to be a sufficient condition for the generation of the EKC hypothesis. The general equilibrium structure of the model allows studying the endogenous evolution of income, emissions and prices of the abatement goods in a unified setting. Originality/value: The paper is novel and original in nature. The results are new in the literature. These results extend and generalise the previous research work in this area in an important way. The sufficient condition that is obtained in this study limits the applicability of EKC in an otherwise identical economy as used in previous literature. Therefore, this paper adds value to the ongoing research related to EKC. [ABSTRACT FROM AUTHOR]

AbstractThe goals of the current study are to analyze the technical efficiency of the Decision Making Unit (DMU) of the cocoa agroindustry and the relationship among technical efficiency, export performance, and competitive strategy in the cocoa agroindustry in Indonesia. Respondents in this study are production and marketing managers at 42 active DMUs. The results show that the average DMU technical efficiency value is 0.963 and 0.985 based on the models of Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS), with the distribution of the full technical efficiency category of 80.95%, the high category of 16.67%, the medium category of 2.38%, and the low category of 0%. This study finds a model for increasing the export performance of the cocoa agroindustry, in which the technical efficiency variable has a significant positive effect on the export performance variable with competitive strategy variables as an intervening variable. [ABSTRACT FROM AUTHOR]

Large shallow intraslab earthquakes (LSIEs) of over magnitude-7 rarely occur at shallower depths (≤ 60 km) in the subducting plates of the circum-Pacific and northern margin of the Australian Plate off Indonesia. Previous studies have suggested that most LSIEs occur under surface tectonic conditions with a lateral stress gradient across the back-arc to the fore-arc on the overriding plate based on seismological and geological evidence. In this study, dynamic conditions for the occurrence of LSIEs were studied using the intraslab stress state, stress state of the overriding plate, motion speed of overriding and subducting plates, and trench migration speed determined by plate motion models. LSIEs prefer tectonic conditions under (1) an extensional-to-neutral stress state in the back-arc, (2) a compressional stress state in the fore-arc, and (3) down-dip tension in the shallower part of the subducting plate. The results suggest that the Earth's subduction zones can be classified into four categories. This categorization is informed by the behavior of underlying mantle flow, i.e., the magnitude of slab suction flow in the mantle under the subducting plates, which is related to the degree of plate-slab coupling, and the scale of return flow in the mantle wedge under the overriding plates, which varies the combination of stress states in the fore-arc and back-arc. [ABSTRACT FROM AUTHOR]

Indonesia is the fourth largest coffee-producing country in the world after Brazil, Vietnam, and Colombia (Richardson et al., 2023). Seeing this opportunity is widely used by business people in making coffee shops (Fahmi & Savira, 2023). This study aims to see the level of efficiency produced by coffee shops with data envelopment analysis (DEA) techniques. This analysis uses input variables, namely labor costs, raw material costs, overall capital, and the amount of labor, and output variables, namely gross profit, and net profit. In DEA using variable return scale (VRS) assumptions where the addition of inputs is not necessarily offset by the output. The sample used was 67 coffee shops in Soloraya. The results of the analysis show that 22 coffee shops have experienced a 100 percent efficiency level while 45 coffee shops have not experienced a 100 percent efficiency level, meaning that those that have not reached 100 percent need improvement in the use of inputs and improved output targets and also benchmarking to make adjustments to their business activities. Managers find it easier to make decisions about whether the business will be saved or increased targets so DEA techniques are more suitable for business people to use in making a decision. [ABSTRACT FROM AUTHOR]

The study aims to compare the environmental efficiency within the group of European Union countries that joined the European Union in 2004 and later, and to identify the common circular economy determinants of efficiency. For this purpose, we performed Data Envelopment analysis and correlation analysis. We applied both constant and variable returns to scale models. Findings reveal that countries with a significant focus on services, particularly tourism, are more environmentally efficient. However, most countries are still heavily industryoriented, with Bulgaria, Romania, and Croatia being the least efficient. The study also highlights the need for significant efforts to reduce greenhouse gas emissions. Interestingly, a positive correlation was found between resource productivity and the circular materials used, suggesting the importance of circular economy tools in improving the environment. Despite having a higher material and consumption footprint, these countries still produce a relatively high product and relatively low CO2 emissions. Based on these analyses, we found regional differences and the need for setting cluster policies within the circular economy at the European Union level. [ABSTRACT FROM AUTHOR]

The issue of productivity and performance in agriculture is significant because it affects a country’s competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified. [ABSTRACT FROM AUTHOR]

The Pact for Life program was one of Brazil's most successful initiatives in coping with an elevated incidence of deliberate lethal violent crimes (CVLI) within the jurisdiction of Pernambuco. It delineated the state into 26 Integrated Security Areas (AIS) and applied strategies to combine investigative and ostensive policing. Nevertheless, the pandemic shifted the production possibility of public security in directions that justify empirical investigations, not sufficiently covered in the current literature. This study employs variable returns to scale data envelopment analysis (DEA) and Malmquist productivity index (MPI) models to measure police efficiency and technology changes from 2019 to 2020. The proposed framework can be particularly suitable to capture changes in the production frontier resulting from technological advancements or regressions, which might otherwise be overlooked. Through a quantitative analysis, this research offers a comprehensive assessment of AISs and the operational performance of the Civil Police, emphasizing efficiency metrics and avenues for enhancement within a production-oriented context. [ABSTRACT FROM AUTHOR]

I estimate aggregate and industry-specific elasticities of scale and markups for the U.S. economy over the period from 1980 to 2019 using data on publicly traded companies. I apply Olley–Pakes and Ackerberg–Caves–Frazer estimation methods and find that the aggregate elasticity of scale for the U.S. economy is 1.1 and has been rising. The elasticity of scale in turn serves as an input for calculating industry markups. Increasing returns to scale help explain observed increases in markups over the last decades for broad sectors of the economy. My estimate of 1.2 for the aggregate markup is significantly lower than the estimate of 1.6 found in recent literature. The large disparity in markup estimates stems from differences in the treatment of fixed and variable costs and the methodological approach to the calculation of markups. • The U.S. economy has been experiencing increasing returns to scale. • The elasticity of scale is estimated at 1.1 and it has been rising. • I use Olley and Pakes (1996) and Ackerberg et al. (2015) estimation methods. • Increasing returns to scale can explain industry concentration and markups. • The aggregate U.S. markups have increased from 1.03 to 1.17 from 1980 to 2019. [ABSTRACT FROM AUTHOR]

The existing research on fixed cost allocation (FCA) in two-stage system data envelopment analysis (DEA) models typically regards the fixed cost as an additional input for each decision-making unit (DMU). However, these models overlook the prevalent real-world scenario where fixed costs act as complementary inputs in production processes. This study proposes a general two-stage network DEA model that incorporates the fixed cost as a complementary input to optimize the allocation scheme. First, we construct a functional relationship between the efficiency scores of DMUs and their allocated fixed costs using a modified super-efficiency DEA model, which effectively classifies DMUs and solves infeasible solutions within the variable returns to scale (VRS) framework. Then, we propose a fair and unique allocation model based on fairness and efficiency maximization principles. Specifically, we allocate fixed costs based on the operational scale for inelastic DMUs while equitably increasing the efficiency scores for elastic DMUs. Finally, a numerical example and an empirical study on subsidy allocation among 30 provinces demonstrate the rationality and acceptability of our approach. [ABSTRACT FROM AUTHOR]

This study assesses the operational efficiency of 14 Sierra Leone commercial banks from 2020 to 2022, focusing on the adoption of financial innovation, such as digital banking, mobile services, and online payments. The research evaluates banks' performance by leveraging innovations using data envelope analysis (DEA) with constant and variable returns to scale models. Findings show varied efficiency, with some banks excelling and others lagging. The study underscores the need for strategic management and optimization so that banks can benefit fully from financial innovations. The insights inform policymakers and bank managers on enhancing the sector's operational performance through technology integration. [ABSTRACT FROM AUTHOR]

As the population increases, spending on publicly provided goods must also increase if there is congestion and governments want to maintain provision of the same level of benefit to everyone. This article estimates a parameter capturing this impact of congestion for the state and local component of the general government sector in Australia. It shows the congestion parameter is likely to be between 0.51 and 0.84 implying super congestion and/or decreasing returns to scale have dominated the supply of these goods. The per person cost of congestion has been rising and differs across states. Larger jurisdictions also have relatively higher per person congestion costs. [ABSTRACT FROM AUTHOR]

This paper focuses on the estimation of efficiency within the medical laboratories industry, a sector of vital importance in healthcare due to its provision of essential diagnostic services. To this end, we employ three distinct stochastic frontier models to evaluate the technical efficiency of the medical laboratory industry. Our benchmark model stands out by considering the presence of heterogeneity, leading to robust findings compared to alternative models. The mean efficiency estimate is determined to be 70.6%, while the median efficiency estimate stands at 70.0%. Remarkably, our results highlight that the production technology employed in US medical laboratories demonstrates constant returns to scale. Moreover, our study delves into the intricate relationship between firm efficiency and market valuation. Our findings reveal a positive and statistically significant correlation between efficiency and market valuation. More specifically, a 1% increase in efficiency corresponds to a 1.08% increase in market valuation. [ABSTRACT FROM AUTHOR]

All-optical thermometry based on laser-driven photoluminescence (PL) of germanium–vacancy (GeV−) centers in diamond is quantified in terms of a trade-off between temperature sensitivity and laser-induced heating. We show that the noise-floor sensitivity η T of the temperature readout from the GeV− PL return scales as (p Δ t) − 1 / 2 with the laser power p and detection time Δ t , allowing the temperature uncertainty to be reduced by increasing p and Δ t. This noise-floor reduction is, however, never penalty-free. Specifically, higher laser powers translate into higher temperatures of the diamond crystal. We demonstrate that the noise-floor as low as η T = 37.5 mK / Hz can be achieved with the laser power set at p = 6.30 mW. We also show that a further reduction of η T is possible at higher p. The experimental setting implemented in this study helps keep the level of heat released in a diamond crystal well below the typical level of microwave-induced heating in nitrogen-vacancy center-based thermometry, thus offering an advantageous approach for diamond-based thermometry in biological systems. [ABSTRACT FROM AUTHOR]

Background: Primary healthcare management efficiency conditions the functioning of specialized care and has a direct impact on the outcomes of the health system and its sustainability. The objective of this research is to develop models to evaluate the efficiency, including health outcomes, of the primary healthcare centres (PHC) of the Clínico – La Malvarrosa Health District in Valencia. Methods: To evaluate efficiency, Data Envelopment Analysis (DEA) was used with output orientation and variable returns to scale, with panel data from the years 2015 to 2019. In rates per 10,000 inhabitants, the inputs are: medical and nursing staff and pharmacy cost. The outputs are: number of consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and pharmaceutical prescription efficiency. As exogenous variables: the percentage of population over 65 years old, over 80 and case-mix. Three models were developed, all of them with the same inputs and different combinations of outputs related to: healthcare activity, outcomes, and both, in order to study the influence of the different approaches on efficiency. Each model is analysed both without exogenous variables and with each of them. Results: The efficiency results vary depending on the model used, although certain PHCs are always on, or very close to, the efficient frontier, while others are always inefficient. When healthcare activity outputs are considered, efficiency scores improve and the number of efficient PHCs increases. However, in general, the PHC score decreases throughout the evaluated period. This decrease is more pronounced when only activity outputs are included. Conclusions: DEA allows the inefficiencies of PHCs to be analysed and the efficient ones are clearly distinguished from the inefficient, although different efficiency scores are obtained depending on the model used. Evaluation can be according to healthcare activity, health outcomes or both, making it necessary to identify the expected objectives of the PHCs, as the perspective of the analysis influences the results. [ABSTRACT FROM AUTHOR]

The efficiency of resource allocation in technological innovation is a critical factor influencing the output level of technological innovation. By expanding and optimizing the Hsieh & Klenow (2009) framework for analyzing the efficiency of resource allocation and relaxing the assumption of constant returns to scale, this study utilizes sample data from Chinese listed companies from 2007 to 2019 to measure and analyze the resource allocation efficiency level in China's technological innovation. The findings indicate that in the process of technological innovation, companies face heterogeneous resource usage costs, leading to a deviation from the optimal resource allocation state, with evident issues of resource misallocation. The loss of efficiency in technological innovation output due to resource misallocation is significant, and addressing this issue can substantially enhance the level of technological innovation output. The misallocation of research and development capital resources is more severe than that of research and development personnel, resulting in greater efficiency losses in technological innovation output. Government subsidies are identified as a significant factor affecting resource allocation in technological innovation. Addressing the issue of resource misallocation, accelerating the market-oriented reforms of technological innovation resource allocation, and optimizing the government subsidy screening mechanism are crucial for improving the efficiency of resource allocation in technological innovation. [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 FROM AUTHOR]

This paper studies how rural-urban migration in China affects the vertical disintegration of firms. We construct a theoretical model and find that the inflow of rural migrants increases the output of firms in urban areas. This leads to a higher degree of vertical disintegration of firms due to the decreasing returns to scale. We also find that the wage of skilled workers relative to that of unskilled workers in urban areas is increased with rural migrants as the vast majority of rural migrants are unskilled. Our empirical findings are consistent with our model predictions using China's population census and manufacturing firm-level data in 2005. [ABSTRACT FROM AUTHOR]

The nonparametric estimator of the Extended Facet reference technology for the Constant Returns to Scale case has attracted some attention, because the associated production frontier by construction does only include strongly efficient faces of maximal dimension, or strongly efficient faces that are part of such strongly efficient faces of maximal dimension. The strongly efficient faces of maximal dimension are denoted Full Dimensional Efficient Facets (FDEFs). The identification of such strongly efficient facets is facilitated by removing all inefficient and all strongly efficient but not extreme efficient DMUs from the estimation procedure of the technology set. Any face that i) is passing through the origin and with (s + m − 1) linear independent extreme efficient observed DMUs positioned on it and ii) with a normal vector with strict positive (strict negative) output (input) components, is a FDEF, where s (m) is the number of outputs (inputs). It is, however, not correct that every face that satisfies only i) is a FDEF. We denote a face (a subface) that satisfies only condition i) but not condition ii) for an AP-face (an AP-subface). It is proved that a radial projection of any output input combination in the estimated EXFA technology set is positioned on the strongly efficient frontier if and only if i) no AP-(sub)faces exist, ii) a regulaty condition RC1 is satisfied and only dual multiplier constraints corresponding to extreme efficient DMUs are included in the estimation. A test for the fulfillment of the condition that no AP-(sub)faces exist is provided. [ABSTRACT FROM AUTHOR]

We study the conditions under which production processes exhibit a decreasing average cost function in the absence of perfectly competitive input markets and discuss some implications for regulatory policy. [ABSTRACT FROM AUTHOR]

Background: Policymakers, who are constantly discussing growing health expenditures, should know whether the health system is efficient. We can provide them with such information through international health system efficiency evaluations. The main objectives of this study are: (a) to evaluate the efficiency of health systems in 28 developed countries by multiple-criteria decision analysis (MCDA) and data envelopment analysis (DEA) and (b) to identify reasonable benchmark countries for the Czech Republic, for which we collect information on the relative importance of health system inputs and outputs. Methods: We used MCDA and DEA to evaluate the efficiency of the health systems of 28 developed countries. The models included four health system inputs (health expenditure as a relative share of GDP, the number of physicians, nurses, and hospital beds) and three health system outputs (life expectancy at birth, healthy life expectancy, and infant mortality rate). The sample covers 27 OECD countries and Russia, which is also included in the OECD database. To determine the input and output weights, we used a questionnaire sent to health policy experts in the Czech Republic. Results: We obtained subjective information on the relative importance of the health system inputs and outputs from 27 Czech health policy experts. We evaluated health system efficiency using four MCDA and two DEA models. According to the MCDA models, Turkey, Poland, and Israel were found to have efficient health systems. The Czech Republic ranked 16th, 19th, 15th, and 17th. The benchmark countries for the Czech Republic's health system were Israel, Estonia, Luxembourg, Italy, the UK, Spain, Slovenia, and Canada. The DEA model with the constant returns to scale identified four technically efficient health systems: Turkey, the UK, Canada, and Sweden. The Czech Republic was found to be one of the worst-performing health systems. The DEA model with the variable returns to scale identified 15 technically efficient health systems. We found that efficiency results are quite robust. With two exceptions, the Spearman rank correlations between each pair of models were statistically significant at the 0.05 level. Conclusions: During the model formulation, we investigated the pitfalls of efficiency measurement in health care and used several practical solutions. We consider MCDA and DEA, above all, as exploratory methods, not methods providing definitive answers. [ABSTRACT FROM AUTHOR]

Societal transformations for addressing climate change are intensely contested and at risk of resistance and backlash to ambitious policy action. But they are frequently modeled through heuristics such as S‐curves which abstract from such conflicts, assuming increasing returns to scale as a driver of transformations. This is the case even while scholars accept the presence of political conflict in transformation processes. Within political science and allied disciplines, the notions of policy feedback and policy coalitions have been deployed to understand how such political conflicts may be understood. But these approaches risk gravitating toward an instrumental design impulse that inadvertently downplays conflict. We argue that policy action for societal transformations should be re‐conceptualized as an unfolding series of battle‐settlement events whereby heated episodic political struggles over a certain policy object or issue play out and eventually settle in ways that structure future debates while nonetheless remaining indeterminate and open to challenge or reversal. Such an approach reflects the varied empirical experiences of climate policy action to date which include both accumulation and reversal. It also helps explain trajectories of change that are discontinuous and lurching in contrast to common images of transformation as progressive and cumulative. We illustrate this approach through two cases of unfolding societal transformation on climate change: coal phaseout in the United Kingdom and renewable energy uptake in Australia. [ABSTRACT FROM AUTHOR]

A key question in economic history is the degree to which preindustrial economies could generate sustained increases in per capita productivity. Previous studies suggest that, in many preindustrial contexts, growth was primarily a consequence of agglomeration. Here, we examine evidence for three different socioeconomic rates that are available from the archaeological record for Roman Britain. We find that all three measures show increasing returns to scale with settlement population, with a common elasticity that is consistent with the expectation from settlement scaling theory. We also identify a pattern of increase in baseline rates, similar to that observed in contemporary societies, suggesting that this economy did generate modest levels of per capita productivity growth over a four-century period. Last, we suggest that the observed growth is attributable to changes in transportation costs and to institutions and technologies related to socioeconomic interchange. These findings reinforce the view that differences between ancient and contemporary economies are more a matter of degree than kind. [ABSTRACT FROM AUTHOR]

An important action to improve the performance of inefficient decision-making units (DMUs) is Finding an efficient target. This target determines the amount of changes in inputs and outputs to achieve efficiency. Although the usual models in data envelopment analysis (DEA) always consider this improvement and present a target as an efficient DMU, but in fact, for some DMUs achieving that target in one step is difficult and even sometimes impossible. For this reason, finding an intermediate target is an important fact in DEA. Accordingly, instead of improving in one step, this work achieves efficiency in several steps; therefore, the improvement is obtained gradually. In this regard, first the efficiency of DMUs is evaluated using the CCR model, and then a sequence of intermediate targets is provided for each inefficient DMU, such that moving in this direction reduces the inefficiency of these DMUs. Also, an example is presented to illustrate the proposed method and its application. [ABSTRACT FROM AUTHOR]

New Flexible Advertising Model Unveiled: Enhancing Advertising Strategies Researchers have generalized the classical Sethi advertising model (1983) to provide a flexible yet tractable approach to optimizing advertising strategies. Unlike traditional methods, the generalized Sethi advertising model is designed to adapt to different market conditions in various media and markets, offering advertisers greater flexibility. By assuming a constant-returns-to-scale relationship between advertising expenditure and untapped market potential, the generalized Sethi advertising model provides advertisers with more options without sacrificing tractability. The research team has made important breakthroughs by developing practical formulas for determining the best advertising strategies for both individual companies and groups of companies. They have also conducted analyses to better understand how different factors influence these strategies. The generalized Sethi advertising model opens up new opportunities for advertisers to fine-tune their campaigns and reach more customers. This research marks a significant step forward in advertising optimization, giving businesses a valuable tool to achieve better results and make informed decisions in their advertising efforts. We propose a flexible yet tractable dynamic advertising model called the generalized Sethi model to capture different market penetration rates across various media and markets via advertising. Specifically, the generalized Sethi model employs a Cobb–Douglas production function of advertising expenditure and the untapped market share with constant returns to scale. It encompasses some standard dynamic advertising models as particular cases. Moreover, the model's flexibility does not compromise its tractability. We demonstrate it by showing single- and multifirm advertising problems involving Nash and Stackelberg games to admit closed-form expressions for the firms' optimal advertising strategies and value functions under the generalized model. Sensitivity analysis of the model parameters also yields novel economic insights regarding the firms' optimal advertising strategies and value functions. Funding: A. P. Kennedy acknowledges the Hong Kong University Grant Council for their support of him pursuing his PhD at the Chinese University of Hong Kong. S. P. Sethi acknowledges financial support from the Eugene McDermott Chair Professorship. C. C. Siu acknowledges financial support from the Research Grants Council of Hong Kong [Grant "Generalized Sethi Advertising Model and Extensions" (Project UGC/FDS14/P02/20)]. S. C. P. Yam acknowledges financial support from HKGRF-14301321 [Project "General Theory for Infinite Dimensional Stochastic Control: Mean Field and Some Classical Problems] and General Research Fund by the Research Grants Council of Hong Kong-14300123 [Project "Well-Posedness of Some Poisson-Driven Mean Field Learning Models and Their Applications"]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0717. [ABSTRACT FROM AUTHOR]

Purpose: To systematically review existing literature regarding the ankle ligament reconstruction‐return to sport after injury (ALR‐RSI) scale and to assess its correlation with Return to sport and functional outcomes as well as feasibility, reliability and consistency. Methods: A systematic review of the literature based on the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) was conducted using PubMed, Embase and Cochrane Library. Studies that evaluated psychological readiness to return to sport after ankle ligament reconstruction or repair for the treatment of chronic lateral ankle instability using the ALR‐RSI scale were included. The results from each study were pooled, and weighted means and overall rates were calculated. Results: In total, 157 patients (53.2% male, mean age: 34.2 years) from three articles were included. Overall, 85.0% of patients reported successful return to sport, but only 48.9% of patients returned to the preoperative sporting level. All studies reported a significant difference in psychological scores between patients who returned to sport and those who did not. Pooled mean patient‐reported outcome measures, reported as the American Orthopaedic Foot and Ankle Society Ankle‐Hindfoot (AOFAS, three studies) Score and Karlsson‐Peterson Score (three studies), were 82.7 (range: 29–100) and 81.7 (range: 25–100), respectively. The ALR‐RSI scale demonstrated strong correlations with the AOFAS Score and Karlsson‐Peterson Score. Conclusion: Patients who returned to sport after ankle ligament reconstruction or repair exhibited higher psychological readiness compared to those who did not. The ALR‐RSI scale showed strong correlations with ankle function. Evaluation of psychological readiness using the ALR‐RSI scale may provide an additional tool in the assessment of patients who underwent ankle ligament reconstruction or repair. Level of Evidence: Level III, systematic review. [ABSTRACT FROM AUTHOR]

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Purpose: The primary objective of this study is to determine how concentrated ownership affects stock returns by country and scale (by market capitalization), like large, medium, and small-cap firms in selected developed economies of the world. Design/methodology/approach: Using a dataset comprising 12,751 annual observations from 850 listed companies from developed economies from 2004 to 2018, the study employs panel data models and instrumental variable estimation to mitigate endogeneity bias. Findings: The findings reveal a significant and positive correlation between ownership concentration and expected returns on corporate equities in developed economies. Furthermore, the study categorizes firms into distinct size categories and finds nuanced differences in the relationship between ownership concentration and stock returns across large, medium, and small-cap enterprises. The results of the study reveal that ownership concentration (by country) and scale (Large, medium, and small) have a significant and positive impact on the stock returns of firms in developed economies. Practical implications: the practical implications of this study extend to investors, firms, policymakers, regulators, and other stakeholders involved in the financial markets. By considering these implications, stakeholders can make informed decisions to enhance market efficiency, investor protection, and overall market integrity. Originality/value: To the authors' understanding, this study is the first to examine the impact of concentrated ownership on excessive stock returns across countries and scales, with an explicit focus on large, medium, and small companies in select developed economies worldwide. [ABSTRACT FROM AUTHOR]

Copyright of Atlantic Review of Economics / Revista Atlántica de Economía is the property of Colegio de Economistas de La Coruna and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study analyzes the economic efficiency of soybean production under contract and non-contract 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. [ABSTRACT FROM AUTHOR]

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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]

When the costs of the inputs and outputs of the units under evaluation are known, the evaluation of the profit efficiency of the units is one of the most significant evaluations that can provide valuable information about them. In this research, first, a new definition of the optimal scale size based on the maximization of the average measure of profit efficiency is presented. The average measure of profit efficiency develops the concept of economic efficiency measure by introducing a more accurate measure of efficiency compared to the measure of comparative and profit efficiency. It has been shown that the average measure of profit efficiency in a convex space is equivalent to the measure of profit efficiency in constant returns to scale technology, and then, some models are presented to calculate profit efficiency in a stochastic environment, to increase the ability of profit models in real examples by considering the calculation errors of inputs and outputs. Finally, the proposed method is used in an empirical example to calculate the average profit efficiency of a set of postal areas in Iran. [ABSTRACT FROM AUTHOR]

As increasing disbursements (such as costs and fees) and risk (such as portfolio risk and leverage risk) may affect managed fund performance, analysts go beyond risk-adjusted return measures for performance appraisal. A methodology that assesses performance in a multidimensional framework is data envelopment analysis (DEA). A variant of DEA is inverse DEA. In this paper, inverse DEA is applied to determine output (investment income and benefit payments) targets for a given fund to perform at a desired efficiency level when increase in disbursements and risk at known levels is envisaged. An output-oriented inverse DEA model assuming variable returns to scale is formulated with theoretical underpinning. The proposed modelling framework ensures that, when an input augmented fund with estimated output targets is included in the observed fund set, the frontier of best performance established with the observed fund set does not change. The inverse DEA model is applied to a sample of Australian superannuation funds to demonstrate how a given fund may obtain pathways to improve its performance under different input-augmentation scenarios. As different pathways suggest feasible output targets, fund managers may find them valuable in forward planning. [ABSTRACT FROM AUTHOR]

Airline efficiency growth is considered one of the key factors for aviation sustainability in Africa and for creating a successful relationship between aviation activities and economic development in the continent. This paper proposes estimating the efficiency of African airlines in the period 2010–2019 using a state-of-the-art stochastic frontier model disentangling persistent efficiency, transient efficiency, and unobserved heterogeneity. We also examine the impact on both persistent and transient efficiency of (i) ownership structure, (ii) political stability, (iii) airline geographical location, (iv) airline domicile country's economic freedom, and (v) airline participation in a global alliance. We find evidence of relatively low efficiency and decreasing returns to scale, implying that it is important to achieve better utilization of inputs. Our findings also suggest that protectionism seems still an important driver of efficiency in a context characterized by a lack of liberalization. However, enhanced economic freedom is found to be more relevant in improving the efficiencies of African airlines, suggesting that policy interventions aimed at speeding up the liberalization process may help to remove the conditions that make air carriers operate inefficiently. [ABSTRACT FROM AUTHOR]

The national independent innovation demonstration zone (NIIDZ) is an independent innovation policy that plays a crucial role in implementing strategies. Given the importance of the NIIDZ, this study uses panel data of 278 prefecture-level cities in China from 2006 to 2020 and empirically examines the effect and internal mechanism of the NIIDZ on green economic efficiency (GEE) using the difference-in-difference model (DID). The results show that the NIIDZ effectively enhances the growth of GEE, and the results remain valid through several robustness tests, such as year-by-year propensity score matching. The transmission mechanism sug‐ gests that the NIIDZ indirectly drives GEE by accelerating scientific and technological investment, promoting talent concentration, and optimizing the industrial structure. Moreover, heterogeneity analysis reveals that the promotion effect of the NIIDZ on GEE is more prominent in the eastern region and high green development level areas. The study’s findings can serve as a reference for China to further utilize the policy effectiveness of the NIIDZ and accelerate the high-quality development of the green economy in the future. [ABSTRACT FROM AUTHOR]

What are the implications of the dramatic fall in IT prices for aggregate technology? When firm-level technologies are continuously differentiable, a factor price shock leads to (i) a substitution between factors and/or (ii) an endogenous response of returns to scale. The second channel is governed by the output elasticity of relative factor demand. Using detailed firm-level data from France, we estimate this elasticity to be positive for IT factor demand. A quantitative exercise accounting for both technological channels shows that falling IT prices can explain much of the changes in concentration and the composition of aggregate labor share in France. (JEL D22, D24, D33, E25, L63, L86) [ABSTRACT FROM AUTHOR]

The document is the front matter of the American Economic Review journal. It includes a list of articles published in the June 2024 issue, as well as information about the journal's editorial board and submission guidelines. The articles cover a range of topics, including the effects of trade deals, education, welfare comparisons, and gender barriers. The journal aims to provide a platform for economic research and is published by the American Economic Association. [Extracted from the article]

Objective: This study examines the productivity and technical efficiency (TE) of diving operations that target queen conches Aliger gigas in the Commonwealth of Puerto Rico, the largest producer of queen conches in the United States. Currently, there is a proposal to list queen conch as threatened under the Endangered Species Act (ESA). Methods: We use stochastic production frontier methods to investigate the relationship between catch and fishing inputs and the technical performance of diving operations. Result: Our results show that the fleet could increase its catches, on average, by 30% (and, thus, increase its income) by using existing fishing inputs and technology more efficiently. We find that the potential to expand catches was slightly higher from increasing the crew size than from extending the length of the fishing trip. The study also finds considerable heterogeneity across coastal regions and operation sizes. Overall, operations on the east and west coasts and those having three or more crew members were more efficient. Operations that use a single gear and specialize on few species (revenue concentration) were associated with higher levels of TE. We also find that diving operations exhibit decreasing returns to scale. Conclusion: The potential ESA listing of the queen conch poses a dilemma because increasing the efficiency of the fleet may continue to compromise the sustainability of the resource. While a threatened designation does not necessarily result in additional trade or harvest restrictions, further actions may be advisable given the many threats, such as overutilization, habitat loss, coastal pollution, and disruptive environmental change that queen conch populations face. Our model suggests that reducing the size of the crew and/or the length of the trip may increase efficiency, but these restrictions may not be advisable on safety grounds. Thus, management agencies may want to reassess existing trip limits and the length of the closed season and explore the use of closed areas. Impact statementThe Commonwealth of Puerto Rico is the largest producer of queen conch in the United States. If queen conch becomes listed as threatened under the Endangered Species Act, managers may have to revisit its management. Understanding the drivers of the productivity and technical efficiency of small‐scale fleets can yield valuable insights into the biological and economic performance of management proposals. [ABSTRACT FROM AUTHOR]

This study presents a novel application of two-stage bootstrap data envelopment analysis (DEA) to assess the efficiency of radiology units in public hospitals. In the first stage of our analysis, we carry out a bootstrap DEA analysis, testing the hypotheses of variable returns to scale to identify efficient units. In the second stage, we examine the effects of four explanatory variables (chief radiology technologist's years of service, presence of customer satisfaction survey systems, age of the equipment, and output variety) other than inputs and outputs on the technical efficiency of radiology units using a bootstrap truncated regression. Counterintuitively, the results show that on average, the use of newer equipment leads to a decrease in productivity and that a chief radiology technologist with greater seniority and the presence of customer satisfaction survey systems do not translate into better productivity. Instead, productivity is positively influenced by the variety of a unit's output. [ABSTRACT FROM AUTHOR]

This study investigates the innovation efficiency of listed companies in the Beijing-Tianjin-Hebei region from 2015 to 2021. Various models are applied to analyze the data and identify factors affecting innovation efficiency. The findings show that, after adjusting the data, most listed companies' scale efficiency decreases significantly. Pure technical efficiency also decreases, but not to a substantial degree. These changes lead to an overestimation of innovation efficiency. The analysis reveals that the business environment influences the innovation index of listed companies. Additionally, there is a positive relationship between enterprise nature, equity concentration, urban financial expenditure, and innovation efficiency. Longer-established companies face challenges in improving their innovation efficiency. Most companies demonstrate improvements in technical efficiency, indicating relatively high levels of technical efficiency. However, continuous technological progress is crucial. The paper suggests that policymakers and company management should prioritize the enterprise's nature, equity concentration, and urban financial expenditure to cultivate innovation efficiency. [ABSTRACT FROM AUTHOR]

This study assessed the marketing efficiency of two crucial fish species in Egypt, the Nile tilapia (Balti) and mullet (Bouri), contributing 73.4% to the nation's total fish production. Utilizing data envelopment analysis (DEA) and the variable returns to scale model, marketing efficiency for the Nile tilapia ranged from approximately 62.4 to 100%, with an average of 87.5%, while mullet fish exhibited a range of 36.2 to 100%, averaging 83.4%. The findings suggest a marketing efficiency deficit of 12.5% for the Nile tilapia and 16.6% for mullet fish, attributable to factors not considered in the model. To enhance efficiency, increasing marketing margins or fish production is recommended. Scale efficiency analysis revealed that some fishers failed to achieve an optimal production efficiency. The Nile tilapia could increase productivity by 24.1%, through optimization at the minimum point on the average total cost curve (MC = AC). Similarly, mullet fish could increase productivity by 27.4%, using the same approach. Furthermore, 70% of the Nile tilapia volume demonstrated increasing returns to scale (IRS), while 25% exhibited decreasing returns to scale (DRS). For mullet, 80% demonstrated IRS, and 10% exhibited DRS. Identified marketing challenges included high summer temperatures causing significant losses, financial constraints, insufficient liquidity, high labor costs, lack of marketing information, and elevated taxes. Recommendations include providing comprehensive marketing information, ensuring well-equipped transportation, attempting to enhance liquidity through lending, and supporting energy to reduce costs for fishing-related activities. [ABSTRACT FROM AUTHOR]

Energy-environmental efficiency directly relates to global climate change and sustainable development. The research applies a staggered DiD design to estimate the effects of low-carbon governance on energy-environmental efficiency via panel data of 284 cities in China. Results show that low-carbon governance significantly improves both unified energy-environmental efficiency and pure energy-environmental efficiency. Heterogeneity analysis reveals that low-carbon governance in central cities has no significant effect on energy-environmental efficiency, while that in peripheral cities can improve energy-environmental efficiency, which indirectly confirms the law of decreasing returns to scale. At the same time, low-carbon governance in both resource-based and non-resource-based cities improves energyenvironmental efficiency. However, among resource-based cities, low-carbon governance in growth and mature cities facilitates energy-environmental efficiency, while this effect disappears in declining and regeneration cities. Mechanism tests suggest that low-carbon governance immediately improves energy-environmental efficiency through intensive energy use and carbon emission reduction channels. The intermediate effect channels are mainly driven by fiscal decentralization, industrial structure upgrading, industrial agglomeration, innovation, and marketization, where fiscal decentralization plays a dominant role. [ABSTRACT FROM AUTHOR]