Using Hybrid Model to Evaluate Performance of Innovation and Technology Professionals in Marine Logistics Industry

With the development of marine logistics industry to grow, the government and corporate more and more attach importance to the performance evaluation of innovation and technology professionals. Combine the characteristics of marine logistics industry and innovative technology professionals to design a performance evaluation index of marine logistics industry in innovation and technology professionals, with the Analytic Hierarchy Process (AHP) to determine the weights of the various performance indicatorsf and through the establishment of fuzzy comprehensive evaluation model to make the problems of complex performance evaluation quantification and then come to their performance evaluation results, and provide reference methods and recommendations for innovation and technology professionals in performance evaluation theory and practice of marine logistics industry

Examining How Manufacturing Corporations Win Orders

[[abstract]]This study adopted 14 criteria for order-winners and qualifiers as the attributes for evaluation. The first stage used a simultaneous importance-performance analysis to analyse the competitive market situations of a corporation and its competitors. The second stage used the decision-making trial and evaluation laboratory method to analyse the attributes’ causal relationships and levels of influence; then two methods of analysis were integrated to analyse and re-formulate the competitive strategies for the winning orders. As well as serving as a novel theory-based method to examine how manufacturers win orders, the proposals in this study can be applied to practical industry experiences.[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]ZA

Green Energy and Applications

Sustainable energy is increasing in importance as Earth’s resources continue to be depleted in an ascending trend year by year. The utilization of sustainable energy is influenced by many factors, such as technology, the economy, and business management. Although it is unaffected by energy shortages, it is influenced by natural conditions—for example, hydraulic, wind, and solar power generation are all necessarily dependent on resource availability. In addition, investment and maintenance costs are high, which has been becoming an important obstacle to the utilization of sustainable resources. Therefore, a number of scientists are seeking new technologies and methods for improving renewable energy, to alleviate the impact of resource shortage on the world’s economy

Design of Research on Performance of a New Iridium Coordination Compound for the Detection of Hg2+

Heavy metal pollution has become one of the most significant pollution problems encountered by our country in terms of environment protection. In addition to the significant effects of heavy metals on the human body and other organisms through water, food chain enrichment and other routes, heavy metals involved in daily necessities beyond the level limit could also affect people’s lives, so the detection of heavy metals is extremely important. Ir (III) coordination compound, considered to be one of the best phosphorescent sensing materials, is characterized by high luminous efficiency, easy modification of the ligand and so on, and it has potential applications in the field of heavy metal detection. This project aims to product a new Ir (III) functional coordination compound by designing a new auxiliary ligand and a main ligand with a sulfur identification unit, in order to systematically investigate the application of iridium coordination compound in the detection of the heavy metal Hg2+. With the introduction of the sulfur identification unit, selective sensing of Hg2+ could be achieved. Additionally, a new auxiliary ligand is also introduced to produce a functional iridium coordination compound with high quantum efficiency, and to diversify the application of iridium coordination compound in this field

An Empirical Study on the Employment Monitoring and Early Warning Mechanism of Medical Graduates in Universities with Big Data and Complex Computing System

Based on the management of big data, the analysis and forecast of the employment demand cycle business situation studied in this article is based on the employment cycle theory and a complete set of employment monitoring, employment evaluation, employment forecasting, and policy selection theories and strategies developed around the employment cycle fluctuations, a specific employment phenomenon. First, systematically evaluate the current state of the employment demand boom, appropriately reflect the hot and cold degree of the employment demand boom, and provide necessary information for the government’s regulatory measures, content, and timing. Secondly, it reflects the regulatory effects of graduate employment monitoring, judging whether graduate employment monitoring measures are properly applied, whether they have the effect of smoothing out employment fluctuations, and promoting the country’s employment demand; in addition, business decision makers can take advantage of the employment demand boom, by monitoring the information provided by the early warning system and timely foreseeing the upcoming macrocontrol measures, so that enterprises’ labor adjustments can adapt to the government’s regulatory measures. At the same time, the model proposes a prosperity index method for monitoring and early warning of the employment demand cycle. After selecting and dividing three types of prosperity indicators, the DI index reflecting the trend of the prosperity change and the CI index reflecting the strength of the prosperity change are calculated and constructed. The national employment demand boom monitoring and early warning signal system predicts the trend of the employment boom cycle outside the sample period. The experimental results show that the cyclic prosperity forecast results are consistent not only with the national employment demand prosperity in recent months, but also with the use of the structural measurement ARIMA (p, d, q) model. The alertness value is close, indicating that this indicator system has a good effect on the national employment demand boom monitoring and early warning

An Empirical Study on Big Data Model and Visualization of Internet+ Teaching

In this paper, we conduct an in-depth study and analysis of “Internet+ Business English” teaching through teaching big data model and visualization and elaborate on the change of educational objectives in the context of Internet education. From the perspective of individual value coordinates, the goal of education is to adhere to the people-oriented, personalized, and comprehensive free development of human beings; from the perspective of social value coordinates, the goal of education is to cultivate innovative talents for social innovation and development; through the multiple perspectives of the curriculum in the context of Internet education, we analyze the goal orientation and value reshaping of the curriculum in the context of educational change. The curriculum of the future will develop toward an intelligent curriculum and introduces the curriculum design and the form of curriculum organization in the context of Internet education. A comparison of the constructed regression and classification of a total of 27 data models reveals that the model constructed based on all data in the integrated education system is the most effective. The multiple linear regression model explained up to 66.5% of the variance in student academic performance; the explanatory power of the social and demographic characteristics dimension variables ranged from approximately 13% to 18%, the personal characteristics dimension variables ranged from 7% to 20%, and the student input dimension variables ranged from 10% to 17%. The highest correct prediction rate of the binary logistic regression model was 69%

Low Carbon Strategy Analysis of Competing Supply Chains with Different Power Structures

This paper investigates the emission reduction performance for supply chain members in both single-channel and exclusive dual-channel cases. Two game scenarios (Manufacturer Stackelberg and Retailer Stackelberg) are examined under different channel structures. Furthermore, we introduce government subsidies as an impact factor of low-carbon strategy adoption. In the single-channel (Case 1), we mainly examine the influence of consumers’ price-sensitivity on channel members’ optimal decisions. In the dual-channel (Case 2), we focus on the joint impact of product substitutability and different channel power structures on the optimal decisions under asymmetric related channel status. The analysis suggests that the Stackelberg leaders always perform better than their corresponding followers before emission reduction, while they may not necessarily yield more benefits after emission reduction. The implementation of low-carbon strategy depends on parameters like product substitutability and channel base demand. Finally, all the supply chain members will encounter a Prisoner’s Dilemma when the product substitutability is relatively high

Dynamic Collection Strategy and Coordination of a Remanufacturing Closed-Loop Supply Chain under Uncertainty

This paper aims to investigate the uncertainty factors that impact the collection strategy of a remanufacturing closed-loop supply chain. The basis of this type of supply chain is the collection of used products, without which the remanufacturing of new products would be out of the question. In this paper, we considered the effect of stochastic disturbance on the collection process in a closed-loop supply chain consisting of a manufacturer and a retailer, in which the manufacturer is responsible for collecting the used products. Considering stochastic disturbance, in this research, we proposed a stochastic collection model, and derived the feedback control strategies for both the manufacturer and retailer. Next, we investigated the evolutionary path and probability distribution of the stochastic return rate. Finally, we proposed a contract to coordinate the decentralized closed-loop supply chain. The results showed that the manufacturer would improve the level of return effort as the intensity of stochastic disturbance increases. However, the disturbance would not affect the pricing strategies of the supply chain members. As a result of the stochastic disturbance, the return rate always hovered around the expected return rate, while the expectation and variance of the return rate remained stable from a long-term perspective. The expected value and variance of the return rate could decrease or increase with time, depending on the value of the initial return rate of the system

Opportunism Motivation of Environmental Protection Activism and Corporate Governance: An Empirical Study from China

In the study of environmental protection issues for more than forty years, research on the impact of financial performance on environmental protection has been one of the important branches. In the framework of principal-agent theory, this paper explores the opportunism motives in a company’s environmental protection activism and the moderating role of corporate governance using the data of Chinese listed companies from 2005 to 2016. The study finds that: (1) the company’s environmental protection activism is driven by the opportunist motives of policymakers who want to mask their inability; and (2) environmental protection activism does not enhance the company’s future performance and value creation capability. Further studies find that corporate governance mechanisms play different moderating roles. Fund Shareholders play a positive governance role and reduce the correlation between financial performance and environmental protection activism. However, independence of the board of directors intensifies the opportunist motives. This paper provides new theoretical explanations for environmental protection decision-making, provides novel enlightenment for the protection of environmental protection policies in developing countries and regions