Search results

Consequence prediction is an emerging topic in safety management concerning the severity outcome of accidents. In practical applications, it is usually implemented through supervised learning methods; however, the evaluation of classification results remains a challenge. The previous studies mostly adopted simplex evaluation based on empirical and quantitative assessment strategies. This paper aims to shed new light on the comprehensive evaluation and comparison of diverse classification methods through visualization, clustering and ranking techniques.

An empirical study is conducted using 9 state-of-the-art classification methods on a real-world data set of 653 construction accidents in China for predicting the consequence with respect to 39 carefully featured factors and accident type. The proposed comprehensive evaluation enriches the interpretation of classification results from different perspectives. Furthermore, the critical factors leading to severe construction accidents are identified by analyzing the coefficients of a logistic regression model.

This paper identifies the critical factors that significantly influence the consequence of construction accidents, which include accident type (particularly collapse), improper accident reporting and handling (E21), inadequate supervision engineers (O41), no special safety department (O11), delayed or low-quality drawings (T11), unqualified contractor (C21), schedule pressure (C11), multi-level subcontracting (C22), lacking safety examination (S22), improper operation of mechanical equipment (R11) and improper construction procedure arrangement (T21). The prediction models and findings of critical factors help make safety intervention measures in a targeted way and enhance the experience of safety professionals in the construction industry.

The empirical study using some well-known classification methods for forecasting the consequences of construction accidents provides some evidence for the comprehensive evaluation of multiple classifiers. These techniques can be used jointly with other evaluation approaches for a comprehensive understanding of the classification algorithms. Despite the limitation of specific methods used in the study, the presented methodology can be configured with other classification methods and performance metrics and even applied to other decision-making problems such as clustering.

This study sheds new light on the comprehensive comparison and evaluation of classification results through visualization, clustering and ranking techniques using an empirical study of consequence prediction of construction accidents. The relevance of construction accident type is discussed with the severity of accidents. The critical factors influencing the accident consequence are identified for the sake of taking prevention measures for risk reduction. The proposed method can be applied to other decision-making tasks where the evaluation is involved as an important component.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

This study aims to propose and demonstrate a practical application of a new three-part holistic sensory evaluation (HSE) method for textiles and apparel based on the senses of sight, touch, hearing and smell. HSE method development was carefully documented, described and successfully applied to evaluate sensory characteristics and consumer perceptions and acceptance of bacterial cellulose (BC), a novel sustainable material for apparel.

In Part One of the HSE method, research participants described the material in their own words based on the senses of sight, touch, hearing and smell. In Part Two, they rated the intensities and their linking for 25 predetermined attributes describing BC. Part Three measured participants’ overall liking of BC and its perceived suitability for apparel and accessories.

Application of the HSE method resulted in an in-depth understanding of BC material. Areas for material improvements and positive characteristics were identified, providing direction for further development. Consumers found BC suitable for accessories and outer-layer garments but not for apparel.

Sensory evaluation of textiles and apparel has traditionally focused on the senses of touch and sight. The new HSE method allows evaluating the full range of sensory characteristics of materials/products and holistically assessing consumer perceptions. The method is especially useful for novel materials and wearable technology. BC has gained increased interests as a novel sustainable material, yet consumer studies have been lacking. This study reports a comprehensive evaluation of BC material from consumer perspective.

Relative performance evaluation (RPE) is a widely practiced employee appraisal process in the services industry. In a global delivery model, teams are spread across different geographical locations. The team members work on various tasks under the guidance of different managers and at times under more than one manager for performing the same task. Such complexities make RPE of the team members quite challenging. The paper proposes a methodical step-by-step approach to simplify the evaluation process without compromising on the rigour.

RPE has followed three different approaches. First is the traditional way, wherein evaluators had a common meeting to discuss and arrive at relative evaluation and ranking of members of the peer group employees. In the second, the number of evaluators and employees in a peer group were split in to 2 subgroups. The evaluators provided independent ratings and rankings. Simple mathematical tool then derived the combined ranking. In the third approach, each evaluator evaluated each employee in the peer group and provided the relative ranking for each employee. Again, mathematical tools provided the final ranking considering inputs from all evaluators. All the three evaluation approaches were analysed through an inter-rater agreement method.

All the three approaches for evaluation provided similar results giving confidence that less time-consuming methods could be adopted by evaluators without compromising on the rigour of the evaluation. The outcome of the exercise proved effective as the complaints reaching the ombudsmen reduced as compared to the earlier years. Considerable evaluation time was also saved. The study described in this paper is carried out in a non-unionized, Indian private sector services firm. Its effectiveness in other set ups is yet to be tested.

The research is carried out in the Indian Engineering services firm operating in the Knowledge based sector. Though study results are encouraging, the adaptability of methodology across different sectors and geographies is yet to be tested. More broad based studies are needed to evaluate suitability across firms and regions.

Relative evaluation exercise is challenging for evaluators. Although openness in evaluation is desired, it also makes evaluators uncomfortable in appearing to be taking sides or being opposing a candidate's ranking. The proposed approach brings in anonymity to each evaluator without scarifying individual evaluation.

The proposed methodology can be deployed across different services industries as the proposed methodology is business domain agnostic. It can be easily ported and tailored to align with an individual organization's evaluation philosophy. The suitability and effectiveness of the method can be studied under various types of firms like manufacturing, private, public, NGO, labour oriented, etc. As the proposed method reduces efforts, the stake holders can focus on understanding the relation between employee performance measurement, employee engagement, and long-term outcomes related to employee performance evaluation.

The proposed employee evaluation method leverages inter-rater reliability and agreement tool as a consensus approach to the relative performance ranking exercise. Such an approach to relative performance ranking is original as no prior studies with such an approach are found in the existing Literature.

The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

In the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.

Based on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.

The authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.

Future research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.

The Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the energy cooperation road unusually tortuous, Kazakhstan in Central Asia has natural geographical and resource advantages, so China–Kazakhstan energy cooperation as a new era of opportunity, providing a strong guarantee for China's political and economic stability. The basic idea of building large-scale nuclear power plants in Balkhash and Aktau is put forward, considering the development strategy of building Kazakhstan into a regional international energy base. This work will be a good inspiration for the investment of nuclear generation.

This study solves the problem of increasing noise by combining Monte Carlo simulation with geometric Brownian motion under complex conditions, adds the measure of investment flexibility and strategic value, constructs the utility function of noise reduction weight based on Gaussian radial basis function and extends the nonlinear problem to the evaluation of nuclear power investment benefit.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.