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The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage, which raises new data privacy concerns. Membership inference attacks (MIAs) are prominent threats to user privacy from DL model training data, as attackers investigate whether specific data samples exist in the training data of a target model. Therefore, the aim of this study is to develop a method for defending against MIAs and protecting data privacy.

One possible solution is to propose an MIA defense method that involves adjusting the model’s output by mapping the output to a distribution with equal probability density. This approach effectively preserves the accuracy of classification predictions while simultaneously preventing attackers from identifying the training data.

Experiments demonstrate that the proposed defense method is effective in reducing the classification accuracy of MIAs to below 50%. Because MIAs are viewed as a binary classification model, the proposed method effectively prevents privacy leakage and improves data privacy protection.

The method is only designed to defend against MIA in black-box classification models.

The proposed MIA defense method is effective and has a low cost. Therefore, the method enables us to protect data privacy without incurring significant additional expenses.

This longitudinal research examines US symphony orchestra sector organizations to determine individual efficiencies in allocating resources (donations, governmental/private funding, etc.) for desirable outputs (concerts, educational programs, community outreach). It provides researchers and managers with a tool for identifying, assessing and mitigating organizational inefficiencies.

This study assesses relative efficiencies in performing arts organizations using Data Envelopment Analysis (DEA), a widely-used nonparametric data-intensive benchmarking technique that determines an optimal “production frontier” of best-practice organizations among their peers and assesses their abilities to turn multivariate inputs into multivariate desired outputs.

This analysis highlights efficiency differences in a wide range of orchestras in converting available resources into performance-related outputs. It provides individual arts organizations with useful results for developing practical benchmarks to achieve organizational efficiency improvement.

This study provides constructive benchmarking guidance for improving efficiencies of relatively-inefficient organizations. Future analysis can expand the scope to utilize a two-stage DEA model to provide more specific guidance to arts organizations.

This pragmatic analysis enables arts/culture institutions to assess their organizational efficiencies and identify opportunities to optimize resources in producing social outputs for their target markets.

Efficiency improvements enable performing arts organizations to provide additional artistic/social services, with fewer resources, to larger audiences.

This research demonstrates the abilities of DEA analysis to assess both a sector and its individual organizations to determine efficiencies, identify sources of inefficiencies and assess longitudinal efficiency trends.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

This paper investigates the asymmetric impact of the real effective exchange rate (REER) on Egypt's real domestic output from 1960 to 2020.

A Nonlinear Autoregressive Distributed Lag (NARDL) model is utilized to isolate real currency depreciations from appreciations and account for the potential asymmetry in the impact of the REER. The analyses account for the various channels via which the REER could affect domestic output.

Results show evidence of a long-run asymmetry in the output effect of REER changes in which only real currency depreciations have a contractionary impact on output, while the REER has no impact on output in the short run.

The Egyptian monetary authority cannot rely on domestic currency depreciation as a policy instrument to boost domestic output.

Unlike most of the previous studies, which assume linearity in the impact of the REER on output, we relax this assumption and hypothesize that the REER changes have an asymmetric effect on the Egyptian domestic output in Egypt. We use a long time span from 1960 to 2020 and control for the potential structural breaks in the REER-output nexus and the various channels through which the REER can affect domestic output.

Do LEGO® SERIOUS PLAY® (LSP) workshops result in improved experience of flow components as well as higher levels of creative output than traditional meetings (MEET)? This research studies the extent to which LSP, as a specialized material-mediated and process-oriented cocreative workshop setting, differs from MEET, a traditional workshop setting. Hypotheses for differences in individual flow components (autotelic behavior, happiness, balance), group flow components (equal participation, continuous communication) and creative output were developed and tested in a quasi-experimental comparison between LSP and MEET.

The study was conducted with 39 practitioners in six teams from various industries. In total, 164 observations were collected during two workshops using the Experience Sampling Method. The creative output was assessed by peer evaluations of all participants, followed by structural analysis and quantitative group comparisons.

The results show that two components of individual flow experience (autotelic behavior, happiness) were significantly higher in LSP, and one of the components of group flow experience (continuous communication) was, as expected, significantly lower. Regarding creative output, the LSP teams outperformed the MEET teams. The study suggests that a process-oriented setting that includes time for individuals to independently explore their ideas using a different kind of material in the presence of other participants has a significant influence on the team result.

LSP can improve the components of participants' flow experience to have an impact on the creative output of teams. In cocreative settings like LSP, teams benefit from a combination of alone time and high-quality collaborative activities using boundary objects and a clear process to share their ideas.

This is the first quasi-experimental study with management practitioners as participants to compare LSP with a traditional and widespread workshop approach in the context of flow experience and creative output.

As the wave of liberalization and deregulation have accelerated to relieve rigid controls over airline routes, capacity, and fare setting regimes, Low Cost Carriers (LCCs) have emerged especially in local aviation markets since the 1970s.

This paper has studied the effects of LCC's entry into the domestic aviation market which was pre-occupied by two major carriers, Korean Air (KAL) and Asiana Airlines. Through a simple model describing two situations, prior and post to LCC's entry, we analyzed changes and trends of each airline's output and profit based on the Cournot and two-stage Stackelberg game equilibrium.

In summary, our conclusion consists of five points: (1) Even though JIN Air's entry reduced KAL's respective output and profit, the more JIN Air produces, the higher the joint-profit of KAL and JIN Air is, (2) From the joint-profit aspect, increasing KAL's output to a level than JIN Air's is more profitable on the Gimpo-Jeju route, on the other hand, increasing JIN Air's output higher than KAL's is more profitable on the Jeju-Busan route, (3) Even though JIN Air's entry increase Asiana Airline's output, the more JIN Air produces, the less Asiana Airlines's profit is, (4) Total output in markets as well as total profits of firms will increase under certain conditions, (5) KAL and JIN Air tend to get caught in an unresolved conflict on level of LCC cost.

This paper aims to build a theoretical model of the impact of farmers’ adoption behavior of soil and water conservation measures on the agricultural output to analyze the impact of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Based on the field survey data of 808 farmers households in three provinces (regions) of the Loess Plateau, this paper using the endogenous switching regression model to analyze the effect of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output. Based on the counterfactual hypothesis, if farmers who adopt soil and water conservation measures do not adopt the corresponding soil and water conservation measures, their average output per ha output will decrease by 2.01%. Then, if farmers who do not adopt soil and water conservation measures adopt the corresponding soil and water conservation measures, their average output per ha output will increase by 12.12%. Government support and cultivated land area have a significant positive impact on farmers’ adoption behavior of soil and water conservation measures.

The research limitation is the lack of panel data.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output.

The conclusion provides a reliable empirical basis for the government to formulate and implement relevant policies.

The contributions of this paper are as follows: the adoption behavior of soil and water conservation measures and agricultural output are included into the same analytical framework for empirical analysis, revealing the influencing factors of farmers’ adoption behavior of soil and water conservation measures and their output effects, enriching existing research. Using endogenous switching regression model and introducing instrumental variables to overcome the endogenous problem between the adoption behavior of soil and water conservation measures and agricultural output, and to analyze the influencing factors of farmers’ adoption behavior of soil and water conservation measures and its impact on agricultural output. Using the counter-factual idea to ensure that the two matched individuals have the same or similar attributes, to evaluate the average treatment effect of the behavior of soil and water conservation measures, to estimate the real impact of adaptation measures on agricultural output as accurately as possible and to avoid misleading policy recommendations.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

The paper investigates the production inefficiency of the US electricity industry in the wake of restructuring and emission reduction regulations.

The study estimates a multiple-input, multiple-output directional distance function, using six inputs: fuel, labor, capital and annualized capital costs of sulfur dioxide (SO₂₎, nitrogen oxides (NO_X) and particulate removal devices, two good outputs – residential and industrial-commercial electricity and three bad outputs – SO₂, carbon dioxide (CO₂) and NO_X emissions.

The authors find that restructuring in electricity markets improves deregulated utilities' technical efficiency (TE). Deregulated utilities with below-average NO_X control equipment tend to invest less in these devices, but above-average utilities do the opposite. The reverse applies to particulate removal devices. The whole sample spends more on NO_X, particulate and SO₂ control systems and reduces its electricity sales slightly. Increased investments in SO₂ and NO_X control equipment do not reduce SO₂ and NO_X emissions, but expansions of particulate control systems cut down SO₂ emissions greatly. Stricter environmental regulations have probably shifted the production frontier inwards and the utilities farther from the frontier over time.

Restructuring and environmental regulations do not make all utilities invest more in emission control systems. The US government should devise other schemes to achieve this goal.

The paper unveils heterogeneous reactions of US electric utilities in the wake of restructuring and emission regulations.