Evaluation and Influencing Factors of Agricultural Green Efficiency in Jianghuai Ecological Economic Zone

Traditionally, in the pursuit of economic development, ecological health was sacrificed, but this is no longer tenable considering the vast environmental damage that is difficult to control and expensive to repair. This is especially true for China’s Jianghuai River Basin (JRB). As a result, this paper uses the slacks-based measure (SBM) directional distance function and the tobit model on panel data from various cities and counties in the Jiangsu section of the HRB to empirically analyze regional green agricultural production efficiency and influencing factors from 2005 to 2019. The results illustrate that agricultural and environmental efficiency fluctuate upward in provincial areas. Still, a downward trend is observed in both redundancy and insufficiency rates of undesirable and desirable output. While this indicates improving regional agricultural and environmental efficiency, there is no readily detectable positive effect of technological progress and technical efficiency on green agricultural production efficiency improvements. Following a full analysis, policy implications are presented and discussed.

Marginal Trade-Offs for Improved Agro-Ecological Efficiency Using Data Envelopment Analysis

Today’s agricultural management decisions impact food security and sustainable ecosystems, even when operating with back-to-basic operations. In such endeavors, policymakers usually need a quantitative tool, such as trade-offs margins, to effectively adjust resource consumption or production. This paper applies the weighted slack-based measurement (SBM-DEA) program to 136 developing countries’ agricultural performance. First, it finds the current agricultural efficiency and then makes marginal trade-offs on desirable-output variables (such as crop yield and forest area) to see the effective changes in undesirable-output (such as methane and nitrous oxide emissions). The results show that choosing effective marginal trade-offs does not deteriorate the relative efficiency of the decision-making units (DMUs) below the efficient frontier line. Thus, such a method enables the decision-makers to determine the best marginal trade-off points to reach the optimal efficiencies and decide which output factor needs special brainstorming to design effective policy.

Energy Efficiency Measurement: A VO TFEE Approach and Its Application

Energy efficiency is crucial to the 2030 UN Sustainable Development Goals (SDGs), but its widely measured indicator, energy intensity, is still insufficient. For this reason, in 2006, total factor energy efficiency (TFEE) was proposed with capital, labor, and energy as inputs and GDP as the desirable output. The later TFEE approach further incorporated pollution as the undesirable output. However, it is problematic to regard GDP (the total value of final products) as the desirable output, because GDP does not include the intermediate consumption, which accounts for a large part of the production activities and may even be larger than the value of GDP. GDP is more suitable for measuring distribution, while VO (value of output) is more appropriate for sustainable production analysis. Therefore, we propose a VO TFEE approach that takes VO as the desirable output instead and correspondingly incorporates the other intermediate materials and services except energy into inputs. Finally, the empirical analysis of the textile industry of EU member states during 2011–2017 indicates that the VO TFEE approach is more stable and convergent in measuring energy efficiency, and is more suitable for helping policymakers achieve the SDGs of energy saving, emissions reduction, and sustainable economic development.

Does Eco-innovation Improve Green Total Factor Productivity of China’s Industry?

The improvement of industrial green TFP is crucial for the sustainability of economy and environment. And the eco-innovation directly improves the industrial green TFP. However, there are few studies on the relation between eco-innovation and industrial green TFP. Based on the relevant data from 2006-2015 of 30 provinces in China, using SBM model this study firstly evaluates the industrial green TFP of each province by measuring the desirable output and undesirable output. Then the eco-innovation is measured by patent application quantity and further divided into breakthrough and incremental innovation by patent quality. The results show that eco-innovation improves the development of green industry in China. The promotion from breakthrough innovation is prominent. However, the incremental innovation restrains the development of green industry in China.

Understanding the Empathy in the Design Thinking Process

Empathy has been referred to as one of the main aspects and the key impact factor of Design Thinking (DT). The DT process allows the outcome to be a technically viable solution, while being a desirable output for the users (consumers of the products) and an economically feasible project. The production in the DT process starts with the user’s desirability to reach pleasurable and better products. A common approach to gain a desirable output is having empathy with the users. The empathy implies understanding the individual's desires (their functional and supra-functional needs). Several techniques have been identified for uncovering the users’ needs and reaching the maximum empathy; albeit it is not achieved straightforwardly. There are lots of products and services in life that are not as delightful, enjoyable and pleasurable as it should be for the end users. The big concern in this context, yet, is to identify the gap in understanding the users’ needs in the empathy approach. In line with this, the present research is an endeavor to identify the issues associated with empathy in the DT process and to recognize the obstacles for deep and real empathy with the end user. This paper majorly revolves around reviewing the Empathy and the DT. Findings acknowledge that misunderstanding is a common phenomenon in the Empathy approach in the DT process and the leading cause for this misunderstanding is attributed to the users’ supra-functional needs. Indeed, it is underscored hereby that misunderstanding the empathy might result in unpleasant senses among the users, as well as leading to producers’ unplanned charges, suggesting that the designers would be urged to minimize misunderstanding in the empathy approach.

Analysis of Operational Efficiency Considering Safety Factors as an Undesirable Output for Coastal Ferry Operators in Korea

In the maritime transportation services industry, marine accidents may lead to fatalities, injuries, and property losses. Coastal ferry operators experience marine accidents and must pay attention to safety to guarantee the sustainability of their business. This study is aimed at analyzing the operational efficiency of coastal ferry operators in Korea from a safety perspective. We designed two slack-based measure of efficiency (SBM) models. One is a normal SBM, which includes only the total passenger volume as the desirable output. The other is a safety-constrained SBM, which includes marine accident records as an undesirable output with the desirable output of passenger transportation performance. We selected 44 coastal ferry operators in Korea that have been continuously operating for five years (2013–2017) as decision-making units (DMUs) and compared their operational efficiency scores. The results showed that the impact of marine accidents on business is greater in DMUs with lower transportation sales than in those with higher sales. This suggests that, while it is important for the government to strengthen safety regulations, a combination of policies that also help small ferry operators to stay in business in the long term is necessary to reduce marine accidents effectively while improving efficiency.

Partial Observer Decision Process Model for Crane-Robot Action

The most common use of robots is to effectively decrease the human’s effort with desirable output. In the human-robot interaction, it is essential for both parties to predict subsequent actions based on their present actions so as to well complete the cooperative work. A lot of effort has been devoted in order to attain cooperative work between human and robot precisely. In case of decision making , it is observed from the previous studies that short-term or midterm forecasting have long time horizon to adjust and react. To address this problem, we suggested a new vision-based interaction model. The suggested model reduces the error amplification problem by applying the prior inputs through their features, which are repossessed by a deep belief network (DBN) though Boltzmann machine (BM) mechanism. Additionally, we present a mechanism to decide the possible outcome (accept or reject). The said mechanism evaluates the model on several datasets. Hence, the systems would be able to capture the related information using the motion of the objects. And it updates this information for verification, tracking, acquisition, and extractions of images in order to adapt the situation. Furthermore, we have suggested an intelligent purifier filter (IPF) and learning algorithm based on vision theories in order to make the proposed approach stronger. Experiments show the higher performance of the proposed model compared to the state-of-the-art methods.

Kinetic Proofreading and the Limits of Thermodynamic Uncertainty

To mitigate errors induced by the cell’s heterogeneous noisy environment, its main information channels and production networks utilize the kinetic proofreading (KPR) mechanism. Here, we examine two extensively-studied KPR circuits, DNA replication by the T7 DNA polymerase and translation by the E. coli ribosome. Using experimental data, we analyze the performance of these two vital systems in light of the fundamental bounds set by the recently-discovered thermodynamic uncertainty relation (TUR), which places an inherent trade-off between the precision of a desirable output and the amount of energy dissipation required. We show that the DNA polymerase operates close to the TUR lower bound, while the ribosome operates ~ 5 times farther from this bound. This difference originates from the enhanced binding discrimination of the polymerase which allows it to operate effectively as a reduced reaction cycle prioritizing correct product formation. We show that approaching this limit also decouples the thermodynamic uncertainty factor from speed and error, thereby relaxing the accuracy-speed trade-off of the system. Altogether, our results show that operating near this reduced cycle limit not only minimizes thermodynamic uncertainty, but also results in global performance enhancement of KPR circuits.

Evaluating the Environmental Performance and Operational Efficiency of Container Ports: An Application to the Maritime Silk Road

A major goal for port authorities, operators, and investors is to achieve efficient operations and effective environmental protection. This is because the environmental performance of a container port is important for its competitiveness and sustainable development. However, the container ports along the Maritime Silk Road (MSR) have caused numerous problems with the rapid development, among which the most significant problem is environmental pollution. In this paper, we aim to measure and compare the environmental performance and operational efficiency of ten major container ports along the MSR, including the ports of Shanghai, Hong Kong, Singapore, Kelang, Laem Chabang, Colombo, Dubai, Barcelona, Antwerp, and Hamburg. We develop an improved, inseparable data envelopment analysis (DEA) model with slack-based measures (SBMs) to evaluate and compare the environmental performance and operational efficiency, and we incorporate the desirable output of container throughput as well as the undesirable output of CO2 emission. Our results show that. Overall. these container ports perform better in terms of operational efficiency than environmental performance. We also provide insights for management and policy makers for container ports with different levels of operational efficiency and environmental performance.

Elimination of Excess Capacity in Monopolistic Competition: An Alternative Approach

Monopolistic competition is a real life market structure in which the elements of both perfect competition and monopoly exist. The paper examines the properties of perfect competition and monopoly under the purview of both conventional and Islamic economics. It finds that perfect competition is permissible in Islamic economic framework but monopoly is not. Monopolistic competition, however, cannot be fully abolished because of its real life relevance. The main problem lying with the monopolistic competition is that each firm preserves the capacity of producing more than what they produce in equilibrium- this is generally known as excess capacity. The current paper proposes a model that eliminates excess capacity and shows how the monopolistically competitive firms may remain at an output level that is socially optimum. The proposed model is a modification of Chamberlin (1933) model. According to the proposed model, the firms will produce socially desirable output if they are given some incentives. Amount of required incentive is the difference between the cost of producing additional units of output and the profit foregone due to the deviation from profit maximizing output level.