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Sustainable development strategies are necessary to ensure sustainable performance even though resources are scarce in a firm. In this study, a two-stage production process is designed to analyze a firm’s performance, including sustainability and marketability, using a two-stage network data envelopment analysis. This process will help managers of a firm understand how to improve sustainability and marketability efficiency. The relationship between environmental investment and firm performance is also investigated using truncated regression. The results show that the environmental innovation score (EIS) and resource use score (RUS) have significant negative relationships with firm performance in the short term due to the fact of additional expenses incurred during the innovative research and development of new products and services. Moreover, the study reveals that the emission score positively affects both sustainability efficiency and marketability efficiency, while EIS and RUS have no effects on the efficiencies. These empirical findings are meant to assist managers in better comprehending the characteristics of business sustainability across industries with varying scales and performance levels, offer better business strategies for resource allocation, and enhance a firm’s performance in the post-pandemic era.

PurposeFirst, this study assesses the link between research and development (R&D) expenses and firm efficiency. Second, this study explores how family control moderates the link between the two.Design/methodology/approachThis study uses two measures of time-based firm efficiency, namely, a window slacks-based measure (WSBM) and a window epsilon-based measure (WEBM) of data envelopment analysis (DEA). Then, 216 firm-year observations are analyzed in the Taiwanese cultural and creative industries from 2005 to 2017.FindingsThis study finds that R&D expenses significantly worsen firm efficiency, and that family control positively moderates this effect. A further test separating the sample into family-controlled and nonfamily-controlled firms indicates that R&D expenses negatively affect the efficiency of nonfamily-controlled firms but positively affect that of family-controlled firms.Research limitations/implicationsThe existing literature has examined the link between R&D expenses and corporate performance. However, the process by which R&D expenses affect corporate performance from a production perspective remains unknown.Originality/valueOverall, this study provides insights for policymakers to scrutinize resource management and R&D expenses from the production and resource-based perspectives.

This study aims to investigate the effects of corporate social responsibility (CSR) on corporate performance in the global retail industry. We adopt the modified data envelopment analysis (DEA) game cross-efficiency approach in assessing the longitudinal efficiency of a sample of 414 listed retail firm-year observations given by Forbes 2000 between 2013 and 2018. The performance result indicates that the Americas retail industry is growing steadily and continues to dominate other regions. Not only the retail industry but all industries in Europe have severe environmental safety rules and management requirements in business operations, hence, Europe also scored high in both the overall environmental index in CSR and all their component indices. Additionally, panel regression revealed that the environmental dimension in CSR is significantly and directly correlated to firm performance. This study’s findings will provide practitioners and policymakers with managerial and strategic implications to enhance their efficiency by applying the CSR dimension in the retail industry.

The main purpose of this study was to explore the impact of peace dividends on global changes in national productivity. First, this study assessed changes in productivity from 2005 to 2014 in various countries at different stages of technological development by using a dynamic semiparametric variant of the Stochastic Nonparametric Envelopment of Data model. Furthermore, the logarithmic linear function established through the public choice approach model was calculated, and the peace dividend was measured for each country. Finally, this study used a panel data regression model to analyze the impact of peace dividends on national productivity. The empirical results revealed that after World War II, numerous countries reduced their defense spending through the transfer of resources and formation of peace dividends because of the global expectation of a peaceful environment. This study found that the results varied according to national characteristics and regional environmental characteristics. However, peace dividends generally had a significant impact on national productivity.

PurposeThe main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA).Design/methodology/approachIt adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital).FindingsThe univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.Research limitations/implicationsThe results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.Practical implicationsOverall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency.Originality/valueFirst, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms.

PurposeFirst, this study assesses firms’ efficiency of transforming intellectual capital (IC) components into firm performance. Second, this study examines (1) cubic S-curve relationship between board independence and IC efficiency and (2) how firm size moderates the cubic S-curve relationship.Design/methodology/approachThis study employs a stochastic nonparametric envelopment of data (StoNED) framework to estimate IC efficiency, which is derived from the estimation process of transforming structural, relational and human capitals into accounting- and market-based performance indicators. This study conducts regression analyses on 1,104 firm-year observations of Taiwanese semiconductor firms over the period of 2011–2018.FindingsStoNED results suggest that sample firms' IC efficiency can be relatively improved by approximately 80%. Regression results indicate that a cubic S-curve relationship between board independence and IC efficiency exists, and firm size moderates the nonlinear effects.Practical implicationsOverall, this study highlights the importance of examining the nonlinear effect of board independence on IC efficiency from the perspective of agency theory, and the moderating effect from firm size, which may suggest availability of resources from the resource-based view of the firm.Originality/valueThis study contributes to the literature through the innovative application of an efficiency-based tool for evaluating IC efficiency. The cubic S-curve relationship between board independence and IC efficiency also points to the policy concerning the appropriate number of independent directors on board.

PurposeThe purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk measures as an exogenous input in the investment-efficiency stage. Second, the current study examines the relationship between intellectual capital (IC) and banks' efficiencies.Design/methodology/approachFirst, this study uses a dynamic network data envelopment analysis approach in investigating the efficiencies of 24 Taiwanese banks in 2007–2018 from two perspectives. Second, this research utilizes various regression techniques, namely, ordinary least squares (OLS), robust least squares and truncated regression, to gauge the impact of IC on banks' efficiencies. Typically, IC is determined based on a monetary value-based measure and value-added intellectual coefficient (VAICTM).FindingsResource-utilization (investment) efficiencies were observed as 0.941 (0.964), thereby contributing to the mean overall efficiency of the sample banks at 0.952. However, the related efficiency changes decline over the sample period, thereby suggesting that the average banks' efficiencies hardly increase. Regression analyses show a significantly positive relationship between IC and banks' overall resource-utilization and investment efficiencies.Research limitations/implicationsOverall, this study suggests that researchers should consider risks when estimating banks' efficiencies owing to their connection to banks' investment performance. From banks' dynamic two-stage efficiencies, this study demonstrated that investments in IC will bring improved future economic benefits.Originality/valueDifferent from prior studies, this study improves banks' efficiency evaluation models by incorporating risk measures and assuming weighted periods for the 2007–2008 global financial crisis. Moreover, the use of monetary value-based measure of IC provides consistent results as the commonly-used VAICTM does.

Following the emergence of the Internet, the Internet of things (IOT) brought about another wave of technological and economic revolutions. Through the lens of the production process, this study utilises the dynamic network slack-based measure model in data envelopment analysis to evaluate 32 IOT companies in Taiwan in terms of their innovation efficiency, operational efficiency and overall efficiency for the period of 2007–2017. Empirical results reveal that the average operational and overall efficiencies of IOT companies in Taiwan have been decreasing considerably since 2008. However, their average innovation efficiency remains stable over the sample period owing to government reductions in enterprise research and development (R&D) tax credit incentives. Through the impulse response function method, this study further confirms that the Statute for Industrial Innovation, which was implemented in 2010 and revised and reimplemented in 2016, specifically, policies concerning enterprise R&D tax credits, affect the efficiencies of IOT companies in Taiwan. Overall, this study reveals the performance evaluation process of IOT companies by showing that their innovation capability affects their operational efficiency. Thus, the government is advised to incorporate innovation measures into relevant industrial policies to achieve policy effectiveness.

Background: The polymorphisms inside microRNA target sites locating in the 3′-UTR region may introduce the micro­RNA-binding changes, which may regulate the gene expression and correlate with the potential diseases. Objectives: We aimed to investigate whether the polymorphisms in microRNA target sites of transforming growth factor beta (TGF-β) signaling pathway genes are associated with the susceptibility of mite-sensitized allergic rhinitis (AR) in a Han Chinese population. Methods: In this case-control study, 454 AR patients and 448 healthy controls were recruited. Three HapMap single-nucleotide polymorphisms (SNPs) were mapped to putative microRNA recognition sites and genotyped by TaqMan allelic discrimination assay. Results: The genotype and allele frequencies of 3 SNPs (rs1590 in TGFBR1; rs1434536 and rs17023107 in BMPR1B) showed lack of significant association with AR. However, in the subgroup analysis, the TG, GG, and TG/GG genotypes of rs1590 exhibited significantly increased risk of AR in the male subgroup (TG: adjusted OR = 1.57, 95% CI = 1.08–2.31; GG: adjusted OR = 1.76, 95% CI = 1.09–2.86; TG/GG: adjusted OR = 1.62, 95% CI = 1.13–2.33). The CT genotypes of rs17023107 might have potential to protect against AR in the patients age of Conclusions: In a Han Chinese population, stratified by age and gender, susceptibility to mite-sensitized AR may be associated with 2 SNPs (rs1590 and rs17023107) in microRNA target sites of TGF-β signaling pathway genes.

This study aims to measure the ability of 29 countries in producing competitive products and services that fulfill individual needs and improve the level of welfare with less utilization of natural resources. We build a two-stage network production process model to investigate the ecology efficiency and social welfare efficiency of the countries and then further discriminate the efficient countries in post-analysis. The two-stage network directional distance function is applied to assess the efficiencies of countries, and the network-based ranking approach is used to further discriminate the efficient countries following the panel data between the years 2013 and 2016. Results show that Poland and Spain are strongly referenced by other countries in the ecology stage, whereas Bulgaria, the United States, and Sweden are leaders in the social welfare stage. A remarkable observation is an absence of countries’ efficiency in both ecology and social welfare efficiencies. Most of the 29 countries have lower efficiency in the social welfare stage than in the ecology stage. This study suggests the strengths and highlights the weaknesses of the countries to help the governments efficiently improve and operate their countries.

This research employs the Meta-Malmquist productivity index Data Envelopment analysis and panel data regression to figure out the performances of the construction industry from Taiwan, Korea, and C...

In the port industry, productivity is one of the vital factors for ports to develop competitiveness and market potential. The paper integrates context-dependent data envelopment analysis and forecasting models to conduct an efficient measurement of 53 Vietnamese ports and predict future performance in the port industry. By using the technique to get the measure of performance, this study builds the ports’ benchmark-learning stepping tools for the inefficient ports to enhance increasingly. The attractiveness and progress scores are resulted to assist the ports in situating themselves. Moreover, forecasting port performance results help decision-makers having more detailed information to make better decisions in their strategies and investments.

PurposeThis study aims to evaluate cargo and eco-efficiency of global container shipping companies (CSCs) and explore the determinants of the CSCs' efficiencies. While the former is derived from the CSCs' operational perspective, the latter highlights environmental issue related to carbon emission reduction.Design/methodology/approachIn the first stage, a two-stage double bootstrap approach of data envelopment analysis (DEA) is applied to derive bias-corrected cargo and eco-efficiency of the top ten global CSCs under the variable returns to scale assumption. In the second stage, ordinary least squares and truncated regression are applied to examine determinants of the CSCs' efficiencies.FindingsThe DEA results reveal that the cargo efficiency of the CSCs is higher than their eco-efficiency by about 2.6% under variable returns to scale in DEA. However, the bias-corrected results show that the difference is 2.9%. The overall average efficiencies suggest that the CSCs can improve their cargo (eco) efficiency by 6.9% (10.8%). In the second stage, the regression results show that the numbers of ship, return on assets and asset turnover ratio are significantly related to both cargo and eco-efficiencies, whereas the total fleet capacity positively affects cargo efficiency.Research limitations/implicationsThe results of this study can help the inefficient CSCs make strategic decisions to improve their performance. For example, their business experience and capacity may be contributing to their efficiencies. However, this study only focuses on the container market among the three main markets, namely, dry bulk, wet bulk and container.Originality/valueThis study highlights an environmental issue in the shipping industry. While CSCs are operating their cargo efficiently in general, they should also put green initiatives into their business operations for the long-term sustainability.

This study aims to evaluate the cargo and eco‐efficiencies of international container shipping companies (CSCs) for the period 2013–2017 for benchmarking purposes. An integration of two‐stage network directional distance function and network‐based approach in data envelopment analysis is utilized to distinguish the efficient operators. Results show that most CSCs are highly ranked in the cargo efficiency stage but lowly ranked in the eco‐efficiency stage and vice versa. This study emphasizes the strengths and weaknesses of each factor of every CSC. Results can help the inefficient CSCs find the areas for improvement by learning from their peers.

This paper examines the effects of asset‐light strategy on the corporate performance of listed Asian telecommunications corporations and the moderating effect of managerial ability on the association between asset‐light strategy and corporate performance. The study applies the dynamic slacks‐based measure (DSBM) model and Tobit regression to measure managerial ability. The empirical results show that asset‐light strategy positively affects corporate performance and that managerial ability has a significant moderating effect on the relationship between the degree of asset‐lightness (DAL) and corporate performance. The findings further show that the greater the managerial ability, the stronger the relationship between DAL and corporate performance.

This paper establishes an industrial upgrading model by dividing the industrial upgrading process into two: the foundation–construction and industrial upgrading stages. Eighty‐one sample countries, from 2006 to 2012, were divided into two groups according to their degree of market freedom. The meta‐frontier method was employed to explore technology gaps in the groups caused by the different markets. It was found that emerging economies with a free market have a better upgrading performance than those with a restricted market, and the efficiency gap between the two groups was seen to be continually increasing.

This study evaluates the management efficiency and quality effectiveness of Taiwanese local auditing institutions (LAIs), whereby two outputs leave the first stage without being inputted to the second stage under the assumption of variable returns to scale. To address these considerations, this study integrates multiplicative efficiency aggregation (MEA) in a two-stage network data envelopment analysis (DEA) model into the form of second order cone programming (SOCP). Under a cone structure, our DEA findings indicate that management efficiency increased, and quality effectiveness decreased over the sample period 2013–2015. Besides, a truncated regression analysis indicates that differences in operating environments, particularly urbanization level and LAIs’ attributes, have significant impacts on the management efficiency of LAIs. The potential applications and strengths of SOCP and MEA-based two-stage network DEA in assessing the LAIs are highlighted.

Several studies employ data envelopment analysis (DEA) in the area of portfolio optimization or stock market efficiency evaluation, however, they have not extended two-stage network DEA to further ...

In this study, an epsilon‐based network data envelopment analysis is employed to construct assessment mechanisms for government performance. Moreover, performance indicators of two dimensions of tax collection efficiency and financial effectiveness are measured. We propose a vector autoregression model in which all economic variables are regarded as dependent variables to address the disadvantages of traditional regression model. The conclusions are as follows: (a) measures of tax collection efficiency deteriorated, whereas those of financial effectiveness improved. (b) In an impulse response analysis of the model, an increase in government‐published land values produced significantly increased tax collection efficiency.

This study examined the innovation ability and business performance of global companies in the aerospace and defense (A&D) industry by using dynamic data envelopment analysis and ranking methods with the DuPont model. Results indicated that compared with business performance, A&D companies exhibit lower scores and higher standard deviations in the innovation ability, which signified that they should first work on reducing the gap in the level of innovation ability. DuPont analysis indicated that typical A&D companies exhibit the highest ROE. Finally, this study offers managers and policymakers detailed insights into potential areas of improvements in innovations, business performance, and profitability.

A critical issue for ensuring long-term sustainability of pension funds is how the Public Service Pension Fund Management Board (PSPFMB) makes entrusting decisions to choose investment trust corpor...

This study employs a two‐stage network data envelopment analysis model to analyze the decision quality and capital magnet efficiencies of 155 mutual funds in Taiwan during the period 2007–2016. The empirical results show that fund managers improved their decision quality; however, their capital magnet efficiency declined. This study also found 10 mutual funds performing in decision quality and capital magnet efficiencies, from which practical suggestions are provided to investors. Finally, this study constructs a market competition matrix to help fund managers (and investors) improve their operating and portfolio performance, plus resource allocation.

This paper investigates how patents and research and development (R&D) spikes affect the corporate performance of 863 firm‐year observations of U.S. biopharmaceutical companies. First, a dynamic data envelopment analysis model is adopted to evaluate the performance of the U.S. biopharmaceutical companies. Then, ordinary least squares regression is used to explore the effects of three patent‐related variables (patent counts, citations, and claims) and R&D spikes on corporate performance. This study finds positive impacts of patent counts, citations, and claims on corporate performance. In addition, the results show that R&D spikes have negative contemporaneous effects and time‐lagged effects on corporate performance.

This study explores the economic performance that vicarious warfare can bring for the aerospace and defence industry. First, this study measures the performance of 22 companies using a nonradial dynamic data envelopment analysis model from 2011 to 2017. Second, this study evaluates whether vicarious warfare can influence the performance. The efficiency analysis suggests rooms for improvements meanwhile, the projection analysis suggests that market value should be significantly increased, and the number of employees should be reduced significantly. The regression analysis suggests that the number of times a country takes a side in wars would positively affect the efficiency of companies.

This paper applies dynamic network slacks‐based data envelopment analysis to measure financial performance based on the interrelationship among investment, financing, and dividend decisions. The empirical results show that financial performance is determined simultaneously by the efficiency of decisions, and sample firms have good performance in investment stage, but need to improve their financing and dividend policies. The proposal financial performance measure explains the multicriteria of decision‐making rather than the single financial ratios. Besides, the research contributes a novel on the significant relationship between firm's ownership structure in the form of managers, government and foreign shareholders, and the firm's financial performance.

Assessing university resource allocation or misallocation is necessary to understand its impact on research and teaching productivity. To achieve this insight, this study conducts a two-stage data envelopment analysis to judge the “teaching and research efficiency” and “revenue efficiency” of 61 universities in Vietnam. We analyze what variables have the most effect on the efficiencies of the universities through improving results. Moreover, this research applies scale elasticity to distinguish the benchmark performance leader among Vietnam universities. Results indicate that universities are more efficient in terms of “revenue efficiency” than “teaching and research efficiency.” The scale elasticity decomposition findings show that multidisciplinary universities perform better than those specializing in science and technology and social science and economics. Finally, the competitive map to performance advancement strategies is exhibited. This map helps the university management to enhance their efficiencies.

To achieve the goal of limiting global warming to 1.5 °C above preindustrial levels, net-zero emissions targets were proposed to assist countries in planning their long-term reduction. Inverse Data Envelopment Analysis (DEA) can be used to determine optimal input and output levels without sacrificing the set environmental efficiency target. However, treating countries as having the same capability to mitigate carbon emissions without considering their different developmental stages is not only unrealistic but also inappropriate. Therefore, this study incorporates a meta-concept into inverse DEA. This study adopts a three-stage approach. In the first stage, a meta-frontier DEA method is adopted to assess and compare the eco-efficiency of developed and developing countries. In the second stage, the specific super-efficiency method is adopted to rank the efficient countries specifically focused on carbon performance. In the third stage, carbon dioxide emissions reduction targets are proposed for the developed and developing countries separately. Then, a new meta-inverse DEA method is used to allocate the emissions reduction target to the inefficient countries in each of the specific groups. In this way, we can find the optimal CO2 reduction amount for the inefficient countries with unchanged eco-efficiency levels. The implications of the new meta-inverse DEA method proposed in this study are twofold. The method can identify how a DMU can reduce undesirable outputs without sacrificing the set eco-efficiency target, which is especially useful in achieving net-zero emissions since this method provides a roadmap for decision-makers to understand how to allocate the emissions reduction targets to different units. In addition, this method can be applied to heterogeneous groups where they are assigned to different emissions reduction targets.

This study applies the epsilon‐based measure method in data envelopment analysis (DEA) to evaluate processes in procuring fighter jets (FJs), which are indicative of the technology and capability of major weapons. Moreover, multidimensional scaling analysis and sensitivity analysis were included to assess the selection of FJs. The DEA analysis indicates that the overall efficiency of the sample of 26 FJs was 0.824 on average. Besides, procurers rely on price and capability to decide which FJ models to purchase. Overall, the evaluation results can be provided to procurement decision makers even in selecting other types of major weapon in a cost‐effective manner.

The purpose of this study is to empirically examine the role of manufacturing in improving innovation efficiency of emerging economies. Emerging economies are developing innovations to promote their industries toward high‐technology sectors to facilitate global competitiveness. Nevertheless, the role of manufacturing is often neglected, which can result in low efficiency in the innovation process. This study constructed a three‐stage innovation model that consists of human capital cultivation, manufacturing development, and innovation production to stress and verify the importance of manufacturing. The experimental results suggest that manufacturing development was a key factor affecting innovation efficiency. A performance improvement strategy map was provided to improve each country's innovation efficiency.

Household animal fat has been linked to increased incidence of cancers compared with vegetable fat. However, few epidemiological studies have associated these two cooking oil types with precancerous genotoxic effects, such as occurrence of micronuclei (MN). This study aimed to explore the association between oral MN frequency and household cooking oil type and whether the association can be attributed to polycyclic aromatic hydrocarbons (PAHs). We collected information about individual cooking oil use, measured genotoxic effects by MN tests and urinary PAHs metabolites (OHPAHs) in 245 nonsmokers. The associations between household cooking oil type and MN frequency and OHPAHs were analyzed using generalized linear models (GLMs) and logistic regression models, evaluating odds ratios and coefficient (95% confidence intervals) (ORs, 95% Cls; β, 95% Cls). The odds of animal fat consumers, rather than vegetable fat consumers, was positively associated with higher MN frequency (OR = 1.94, P 0.05). The associations were discovered in participants only using kitchen ventilation (OR = 2.04, P 0.05). Animal fat consumers had higher total OHPAHs than vegetable fat consumers (1.58 ± 0.22 mg/mol, Cr vs 1.20 ± 0.12 mg/mol, Cr; P = 0.028). Significant correlations were observed between total OHPAHs quartiles and increased MN frequency (β = 0.38, P-trend = 0.026). After stratifying by household cooking oil type, sensitivity analyses showed that the positive association between total OHPAHs quartiles and increased MN frequency was only observed in animal fat consumers (β = 0.61, P-trend = 0.030). In conclusion, usage of household animal fat was associated with an increased odds of oral MN frequency in Chinese nonsmokers and the odds correlated with increased PAHs exposure. This finding supplemented evidence associating cooking oil type with genotoxic effects and explained its association with PAHs exposure.

PurposeThis study examines the effect of value-added (VA) intellectual capital on business performance from the perspective of productive efficiency, which is derived from its main contributors, namely, profitability and marketability efficiencies in two stages.Design/methodology/approachFirst, this study applies a dynamic network slacks-based measure in a data envelopment analysis (DEA) approach to estimate productive efficiency and its components of 766 Taiwan listed electronics companies over the period of 2010–2018. Second, this study performs regression analyses of the association between intellectual capital (IC), which is proxied by VA intellectual coefficient (VAICTM) and estimated DEA efficiency scores through various regression techniques.FindingsEmpirical evidence shows a significantly positive association between VAICTMand productive efficiency. This study finds the same result from the IC components after splitting VAICTMinto (1) IC efficiency, which comprises human capital efficiency (HCE) and structural capital efficiency and (2) capital employed efficiency. Further examination reveals that HCE is the sole main contributor of the productive efficiency, and profitability and marketability efficiencies of a company.Practical implicationsThe findings of this study highlight the need to discuss the values of intellectual coefficient (IC) from the perspective of productive efficiency for better comprehensiveness.Originality/valueAlthough previous studies have shown that IC is a contributor of business performance, this study further zooms in VAIC and examines its effect on the efficiency of a company in transforming its inputs into outputs.