Output Mix Research Articles

Specialty economies of scope in English hospitals: Cost Arguments for colocation

ObjectiveCurrent policy responses to COVID-19 disruption and care backlogs suggest potential changes to the location and structure of hospital healthcare supply. However, few studies investigating the cost effects of hospital reorganisation consider changes in the mix of outputs or test for the existence of economies of scope in hospital healthcare. Attempts to create dedicated hubs to address healthcare demand backlogs could have unintended adverse cost effects where these are provided outside existing hospital arrangements. To evaluate this, we investigate the existence and size of economies of scope in English hospital healthcare. DataWe use cost and activity data from the English NHS, linked to aggregated staff wage information and information taken from hospital financial statements. Cost and activity data was obtained from NHS England's Costing Publications. Wage data was extracted from the NHS's Electronic Staff Record via the NHS England Workforce Statistics Team, and published hospital financial accounts were aggregated and linked together at the organisation level. ResultsGeneral Surgery exhibited positive economies of scope when provided alongside other healthcare, as to a lesser extent did General Medicine and Obstetric/Gynaecology healthcare. There was little evidence for economies of scope in Diagnostic and Pathology services, Orthopaedics, or Emergency Care. Few (2/28) output cross-products (cost complementarities) were statistically significant, but Baumol's wider definition of scope economies demonstrates that scope economies are present in some specialties. ConclusionPolicymakers seeking to maximise the amount of healthcare provided and minimise the costs of doing so may wish to consider retaining General Surgery, General Medicine and Obstetric/Gynaecology healthcare supply alongside the provision of other clinical specialties. There is limited evidence that reconfiguring supply by centralizing other specialty groups into fewer providers would increase costs.

Terahertz Replica Generation of Ultra-High Data Rate Transmission in an Electro-Optical Semiconductor Optical Amplifier Mach–Zehnder Interferometer System

This article presents an analysis of an electro-optical up-converter relying on a semiconductor optical amplifier Mach–Zehnder interferometer (SOA-MZI). The pulsed control signal is generated by an optical pulse clock (OPC) with a repetition rate of fs= 19.5 GHz. The intermediate frequency (IF) signal, which carries the modulation format known as quadratic phase shift keying (QPSK) at a frequency fIF, is shifted at the output of the SOA-MZI to high outlet mixing frequencies nfs±fIF, where n represents the harmonic order of the OPC. To examine the characteristics of the sampled QPSK signals, we employ the Virtual Photonics Inc. (VPI) emulator and evaluate them using significate metrics like error vector magnitudes (EVMs), conversion gains, and bit error rates (BERs). The up-mixing process is mainly achieved through the cross-phase modulation (XPM) effect in the SOA-MZI, which operates within a 195.5 GHz ultrahigh frequency (UHF). The electro-optical SOA-MZI up-converter demonstrates consistent uplifting conversion gains across the scope of the output mixing frequencies. The simulated conversion gain deteriorates from 38 dB at 20 GHz to 13 dB at 195.5 GHz. The operational efficiency of the electro-optical SOA-MZI design, employing the standard modulation approach, is also evaluated by measuring the EVM values. The EVM attains a 24% performance level at a data rate of 5 Gbit/s in conjunction with the UHF of 195.5 GHz. To corroborate our results, we compare them with real-world experiments conducted with the UHF of 59 GHz. The maximum frequency range of 1 THz is attained by increasing the OPC repetition rate. Ultimately, through elevating the control frequency to 100 GHz, the generation of terahertz replicas of the 4096-QAM (quadrature amplitude modulation) compound signal becomes achievable at heightened UHF, extending 1 THz, while maintaining a data transmission rate of 120 Gbit/s and upholding exceptional performance characteristics.

Robust low-rank learning multi-output regression for incipient sediment motion in sewer pipes

The existing incipient sediment motion models typically apply conventional regression methods considering either velocity or shear stress. In the current study, incipient sediment motion is analyzed through a simultaneous and joint analysis of velocity and shear stress using the robust low-rank learning (RLRL) multi-output regression technique. Moreover, the experimental data compiled from five different channels are utilized to develop a generic incipient sediment motion model valid for a channel of any cross-sectional shape. The efficiency of the developed method is examined and compared against the available conventional regression models. The experimental results indicate that the RLRL model yields better results than its counterparts. In particular, while cross-section specific models fail to provide accurate estimates for shear stress or velocity for other cross sections, the proposed model provides satisfactory results for all channel shapes. The better performance of the recommended approach can be attributed to the joint modeling of the shear stress and the velocity which is realized by capturing the correlation between these parameters in terms of a low rank output mixing matrix which enhances the prediction performance of the approach.

Limiting flexibility in nonparametric efficiency evaluations: An ex post k-centroid clustering approach

An attractive feature of standard data envelopment analysis (DEA) is that decision-making units (DMUs) are put in their best possible light. This is accomplished by not imposing any restrictions on how the inputs and outputs can be weighted together. Unfortunately, this flexibility also has drawbacks. The underlying best practice production structure is typically very complex, which can make it difficult to understand efficiency evaluations. This flexibility may also motivate DMUs to pick specialized input‒output combinations simply to appear more efficient, particularly in applications where they are rewarded based on their DEA performance. In this paper, we therefore propose an approach that retains the fundamental principles of DEA while reducing flexibility in the evaluations. Our approach entails performing ex post k-centroid clustering of DMUs according to their input‒output mix patterns. The resulting mixed-integer programming problem seeks to put the centroids (as prototypes of their generated clusters) in their best possible light. This clustering enables us to work with a less complex underlying technology, which simplifies the evaluations and enhances their interpretability. Furthermore, it limits the possibility of DMUs inflating their performance by selecting extreme input‒output combinations. We demonstrate our approach with a simple numerical example and a complex data set involving Brazilian electricity distribution companies, providing clear and realistic illustrations of its application.

Measuring Changes in Chinese Banking Productivity and Profitability

Abstract This paper adopts the Hicks-Moorstein (HM) TFP index and Data Envelopment Analysis (DEA) to explore efficiency and its relation to changes in profitability and productivity in Chinese commercial banks (CBs). We decompose the HM TFP index into changes in technology, pure technical efficiency, scale efficiency, and output mix and then test for distribution differences when comparing the Malmquist and Hicks-Moorstein productivity indices for a given type of data. The study results reveal that the CBs experience primarily an increment of mix-efficiency rather than an improvement in pure technical efficiency (improvement in management practices) and that Chinese CBs pursue technological progress to meet the requirements for financial innovation and internet banking. This paper highlights the importance of analyzing performance from multiple perspectives and provides alternative explanations of improving productivity and profitability based on technical efficiency in general. Our results indicate that including non-performing loans as the input increases the efficiency score, but off-balance sheet items do not have a significant impact. JEL classification numbers: D24, E58, G24. Keywords: Trading Conditions, Hicks-Moorsteen(HM) TFP index, Data Envelopment Analysis (DEA), Productivity, Profitability.

Effect Factors on Unconfined Compressive Strength of Soil-Cement Columns: The Case Study of Ba Ria, Vung Tau, Vietnam

This paper presents the effect of the curing environment on the unconfined compressive strength of soil-cement samples and in finding the optimum output mix ratio and estimating the effect of silica fume in the admixture. This work is based on the data from the Cai Mep-Thi Vai inter-port road project and results from laboratory experiments. The results show that the specimens with the highest strength were cured in soil, lowered in city water with NaCl 2.5% and then NaCl 5%. The optimum silica fume admixture ratio equals to 1% (in comparison with the weight of cement content).

Identifying optimal capacity expansion and differentiated capacity payments under risk aversion and market power: A financial Stackelberg game approach

We investigate how capacity payments in combination with scarcity pricing of energy can ensure resource adequacy in electricity markets, defined as the ability of supply and other resources to provide enough energy and capacity to meet demand under steady-state operating conditions. This work generalizes models for determining capacity payments by deriving second-best discriminatory payments by resource type that account not only for the “missing money” market failure that arises from energy price caps, but also for market power in the capacity market and differences in risk tolerance among resource types that can arise from failures in risk and capital markets. A bi-level equilibrium-constrained optimization model is proposed to define second-best capacity payments in a static long-run setting, considering the impacts of those payments on the mix and cost of generation investment and energy outputs. The lower-level suppliers play a Nash game to determine the generation mix under a capacity payment scheme, while the upper-level regulator considers consumer welfare and resource adequacy. We introduce an equivalent formulation via a variational inequality approach, and find conditions for the solution to exist. Discriminatory payments are found to be second-best when there are market power in the investment game, price caps in energy markets and imperfections in risk markets that lead to diverse risk attitudes.

Scale and Scope Economies in Banking: A Case Study of the Agricultural Development Bank of Pakistan

This paper examines the scale and scope efficiency of the Agricultural Development Bank of Pakistan. Using the production approach to measuring bank outputs and costs, a translog cost function is estimated to provide an assessment of the bank’s scale and scope efficiency, and to quantify the extent to which its production costs are sensitive to size and output mix. Our results show that the bank enjoys both overall and product-specific economies of scale and, therefore, there exists scope for the bank to expand its operations at declining average cost. We show that even though bank branches in all size categories enjoy economies of scale, the extent of such economies is larger for branches operating at a smaller scale of production. This implies that as the bank branches grow larger in size in terms of both loan and deposit accounts, they move closer to attaining constant returns to scale. It is also shown that the marginal costs of servicing both loan and deposit accounts decline as bank branches grow larger in size in terms of either the number of loans or the number of deposits. This confirms that branches operating at a larger scale of production have attained greater cost efficiency in terms of servicing the loan and deposit accounts. As regards economies of scope, our results show that the bank’s production technology is characterised by cost complementarity, which gives rise to cost savings through the joint production of loan and deposit accounts.

EFFICIENCY OF ISLAMIC BANKS: EVIDENCE FROM ISLAMIC WINDOWS OF CONVENTIONAL BANKS IN ETHIOPIA

The study examines the cost and technical efficiency of selected Islamic banking windows of conventional banks in Ethiopia during the period of 2016-2020. The parametric method, stochastic frontier approach (SFA) was employed to measure both cost and technical efficiency of the banks. The efficiency scores of the sampled banks can be measured based on their performance in utilizing inputs to successfully generate output during the study period. It gauges the service quality of the banks taking loans and deposits as well as operating income and expenses into consideration. The study uses time series data from four conventional banks which provide Islamic banking widow in Ethiopia. The statistical findings show that the conventional banks have fairly better technical efficiency individually and collectively; however, the cost efficiency scores indicate that the banks are not efficient enough in terms of minimizing costs for a given scale and mix of outputs. Similarly, the results of the stochastic technical frontier estimates uncovers that there is positive significant relationship between the input variables namely total deposits and total operating expenses and output variables namely total financing and total operating income. The outputs remain an essential contributor to the cost efficiency in Islamic windows conventional banks in Ethiopia.

How do endowments determine trade? quantifying the output mix, factor price, and skill-biased technology channels

Differences in how countries absorb endowments of skilled and unskilled labour can be decomposed into (a) differences in the skewness of output mix towards skill-intensive industries and (b) differences in the skill intensity of each industry. The latter can be decomposed into contributions from cross-country differences in (2a) relative wages and (2b) skill-biased factor-augmenting technologies. To investigate the relative importance of each, we develop a multi-sector Eaton-Kortum model featuring skilled/unskilled labour and factor-augmenting international technology differences. The model is calibrated to WIOD data for 39 countries in 2006. Using a model-based decomposition, we show that the skill-intensity mechanism is much more important than output-mix. Further, differences in skill intensities across countries are explained in similar proportions by the relative-wage mechanism and the technology mechanism. Our results have immediate implications for the impact of endowments and skill-biased technology on output mix, trade in goods, and international differences in skill premia.

Disentangling the sources of dynamics in the agricultural output of the BRIICS and EU countries: The ecological footprint perspective with Shapley value decomposition

Agricultural production and productivity are important from multiple perspectives, including environmental protection, food self-sufficiency, renewable energy sources as well as economic returns. The earlier literature has sparsely addressed the biological and economic productivity dynamics when decomposing the changes in the output of agriculture within a single framework at the country level. This paper presents an index decomposition approach that allows explaining the changes in agricultural output from the perspective of the ecological footprint and biological capacity. These measures represent the shift towards a more valuable output mix and lower environmental pressures. Economic and biological productivity is involved in the analysis. The case of the selected European Union (EU) and BRIICS (Brazil, Russia, India, Indonesia, China and South Africa) countries is considered for the empirical analysis. The index decomposition analysis model based on the Shapley value is constructed for the empirical analysis. The results suggest that the EU countries saw a less vibrant growth in the agricultural output than that of the BRIICS countries over 1992–2016. The biological productivity growth was more important for the EU countries if opposed to the BRIICS ones.

Multi-target regression via non-linear output structure learning

The problem of simultaneously predicting multiple real-valued outputs using a shared set of input variables is known as multi-target regression and has attracted considerable interest in the past couple of years. The dominant approach in the literature for multi-target regression is to capture the dependencies between the outputs through a linear model and express it as an output mixing matrix. This modelling formalism, however, is too simplistic in real-world problems where the output variables are related to one another in a more complex and non-linear fashion. To address this problem, in this study, we propose a structural modelling approach where the correlations between output variables are modelled using a non-linear approach. In particular, we pose the multi-target regression problem as one of vector-valued composition function learning in the reproducing kernel Hilbert space and propose a non-linear structure learning approach to capture the relationship between the outputs via an output kernel. By virtue of using a non-linear output kernel function, the proposed approach can better discover non-linear dependencies among targets for improved prediction performance. An extensive evaluation conducted on different databases reveals the benefits of the proposed multi-target regression technique against the baseline and the state-of-the-art methods.

A new parallel processing architecture for accelerating image encryption based on chaos

This study introduces a novel parallel processing architecture for accelerating image encryption based on chaos. In the proposed architecture, whole image data is split into partitions of particular size to create separate encryption threads. As the proposed cryptosystem employs several identical chaotic ciphers running concurrently and independently to process the partitions, it greatly leverages the degree of parallelism to some extent. A powerful output mixing logic based on an additional chaotic function, and simple exclusive-OR and shift operations is innovatively incorporated to ensure inter-partition diffusion. Since there is no dependency on previous data bytes in the introduced logic, blending operations applied on the outputs of independent encryption threads can be concurrently executed by exploiting loop-level parallelism to the extent allowed by data processing units available. The number of blending operations that should be carried out for an image is kept proportional to the partition size which also directly determines the number of separate encryption threads created. In order to measure encryption/decryption runtimes, the proposed architecture has been tested on two different multi-core CPUs, namely 4-core and 8-core. The obtained results show that the proposed cryptosystem parallelising sequential operations by introducing a multi-threaded encryption architecture is much faster than the base cipher and most of the other state-of-the-art algorithms. Having successfully passed various security tests, the proposed cryptosystem manifests its robustness against cryptographic attacks, and hence become evident that it is efficient for secure transmission.

Understanding performance change of the water industry: how do size and patterns of output mix associate with efficiency?

ABSTRACT The water and sewerage industry in England and Wales had undergone several reforms since its privatization. To evaluate to what extent they had impacted on the performance of water companies, an input distance function and its derived cost share equations was estimated. This allowed measuring technical efficiency, economies of scale and cost complementarities between water and sewerage services over the period 1991–2016. The results indicate that an average water and sewerage company (WaSC) reported a technical efficiency score of 0.731 which means that its inputs could be reduced by 26.9% over time. It is also shown that an average WaSC operated under decreasing economies of scale. Cost complementarities between water and sewerage connected properties were found. This implies that WaSCs could benefit from remaining integrated, i.e. providing both water and sewerage services.

Differences between the productivities of organic and conventional dairy farms in Denmark

Abstract The study compares the productivity change over time of organic and conventional dairy farms in Denmark between 2011 and 2018 using data envelopment analysis, and aims to identify which technology is superior. Productivity changes and the differences between organic and conventional frontiers in each year for observations from each group are calculated for each technology separately using the Malmquist Productivity Index and its components. Then, a recently developed permutation test is used to analyse the statistical significance of the results. The analysis identifies volatility in the (economic) production possibilities, which is likely related to changes in milk prices caused by geopolitical events, which the conventional technology seems to be more susceptible to. Furthermore, the organic technology on average became superior for conventional farms in 2015. Farm level analysis identifies characteristics of the input–output mix of the farms, indicating whether a farm could benefit from conversion to the other technology.

Comparing group performance over time through the Luenberger productivity indicator: An application to school ownership in European countries

This paper extends the Camanho and Dyson (2006) one-period Malmquist-type index (CDMI) and the recent pseudo-panel Malmquist index (PPMI) by Aparicio et al. (2017) and Aparicio and Santín (2018) to a context where additive efficiency measures are used. In particular, we apply the Luenberger productivity indicator. Unlike the CDMI, the new approach is based upon the directional distance function, allowing non-equiproportional changes in the input and output mix and variable returns to scale for comparing the efficiency and technology gaps of two or more groups of production units over time. To illustrate this methodology, we estimate how the productivity gaps between publicly funded private schools (PFPS) and public schools (PS) in eight European Union countries changed over the 2009–15 period using PISA data. Our results suggest that the performance of PFPS is better in Belgium, Ireland, the Netherlands and Spain in both waves, while PS productivity outperforms PFPS in the Czech Republic, Hungary and Slovakia. Both school types operate with a productivity gap close to zero in Denmark. In addition, we observe that despite being less efficient, PS are more productive than PFPS, thanks to their better production technology. Finally, we find that school autonomy is positively related to school productivity explaining why PFPS present higher productivity than PS in some countries.

Efficiency and productivity analysis of pineapple farmers in the Akwapim-South District of Ghana: A distance function approach

The study sought to analyze the efficiency and productivity of pineapple farmers in the Akwapim-South District of Ghana. The paper employs the stochastic translog distance function technique to analyze the influence of inputs on outputs whilst highlighting the technical efficiency and its determinants of the pineapple farmers. A total of 135 respondents were randomly selected using the multi-stage sampling technique. The results reveal that all the input variables (fertilizer, labour, cost of pineapple suckers and intermediate cost) are significant and have a positive influence on the productivity of pineapple production. The shadow share of other crops is estimated to be negative relative to the production of pineapple in the output mix. The mean technical efficiency score is found to be 85%. This implies that pineapple farmers in the Akwapim-South District have the potential to increase their output level by 15% using the current technology available to them. The results further indicate that age, number of extension visits, education and FBO (farmer-based organization) membership significantly and positively affect the technical efficiency of pineapple farmers. The paper recommends that government policies should ensure inputs are available to farmers at subsidized prices. Furthermore, regular education of extension agents and properly structured extension and FBO service delivery systems should be put in place to enhance the productivity of farmers.

Decomposition of energy intensity in Chinese industries using an extended LMDI method of production element endowment

The purpose of this paper is to decompose the impacting factors of production element endowment (PEE) on energy intensity in China’s industries in 2000–2015. This is vital for China’s policy-making in terms of the development of low-energy-consumption (LEC) industries under relatively rapid industrialization and urbanization. This study contributes to the comprehensive investigation of PEE’s impact on energy intensity (EI), which can bridge the existing literature gap.A PEE extended logarithmic mean Divisia index (LMDI) method was developed to decompose the changes in the Chinese industrial EI into three PEE, two intensity, and two structure factors. These driving factors include the energy–capital ratio (EK), capital–labor ratio (KL), labor–technology ratio (LT), R&D intensity (RI), investment intensity (II), energy mix (ES), and share of provincial industrial output (OS). The results demonstrated the following. (1) Overall, the effects of LT and EK are the two leading contributors to the decline in EI in Chinese industry. Moreover, OS exerted a negative effect on EI, and ES showed a marginal negative effect on EI. KL, II, and RI played roles in the increase in Chinese industrial EI. (2) In terms of the cumulative effects at the provincial level, LT and KL had the largest curbing and stimulating effect on the EI of all provinces, respectively. EK, II, RI, and OS had positive or negative effects on EI in all provinces with some fluctuations. Among all factors, the ES effect was the weakest and demonstrated mixed results in different provinces. (3) In the eastern, central, and western regions, LT, EK, and OS decreased Chinese industrial EI. KL, II, and RI were the three major contributors to the improvement in EI. Finally, the policy recommendations for EI reduction in Chinese industry are presented on the basis of the empirical results.

Informality and structural change: evidences from microenterprises in India's unorganised manufacturing sector

PurposeThis article analyses the structural change in microenterprises located at India's unorganised manufacturing sector in terms of output mix, choice of technique and productivity during the last few decades.Design/methodology/approachBased on data collected from a quinquennial survey of unorganised firms, this study attempts productivity analysis by using the growth accounting technique.FindingsThe paper finds that there is a significant structural change which has occurred in the small firm sector in Indian manufacturing. The share of capital-intensive industries has increased substantially in recent years. Further, though small firms are more labour intensive, the labour productivity and total productivity of these firms are very low. The falling labour productivity and rising capital intensity indicates replacement of labour with capital in Indian small firm sector.Practical implicationsLow productivity of the sector is a cause for concern and this needs to be addressed by making the sector more competitive in the world market. To achieve this, policies should be designed so that small firms reach the efficient scale of production.Originality/valueThis is the first paper which examines structural changes in the Indian MSME sector. The findings have strong implications for creation of a viable ecosystem of entrepreneurship in the country.

Profit Efficiency of the South Australian rock lobster fishery: A Nerlovian and directional distance function approach

Efficiency analyses are used in fisheries to understand the contributions of inputs, outputs and management to productivity. Previous efficiency analyses have mainly focused on productivity, cost and revenue, with relatively few investigating profit efficiency that enables analysis of the mix of inputs and outputs. Negative profits and small sample sizes in fisheries have been some of the obstacles diverting attention from this direction. We consider a new approach in the context of fisheries to overcome these challenges and examine profit efficiency in the South Australian rock lobster fishery. Specifically, we apply Nerlovian and directional distance function methods to decompose profit efficiency of the rock lobster fishery into technical and allocative efficiencies. We use local and meta-frontier efficiency techniques to compare the northern and southern zone rock lobster fisheries. In contrast to observations based on profit levels, the profit efficiency analysis shows no significant difference between northern and southern zones. In addition, we examine the effect of implementation of a quota system in the north to match the south and find that biological conditions hindered efficiency gains being fully realized after the implementation of the quota system.