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For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

The purpose of this study, the nonlinear relationship between the real estate market and the stock market was investigated in Iran. For this intent, the monthly data from 2012:4 to 2022:5 is used.

In this study, the quantile-on-quantile estimation method is used, which is a combination of the nonparametric estimation methods and the quantile regression.

The research results show that, in the low quantiles, the effect of stock market return on the housing market return is negative or zero. In fact, in this situation, the increasing returns in the stock market will shift part of the financial resources of the economy to the market and create stagnation or even negative returns in the housing market. This situation is seen more strongly in some other quantiles, including the 0.25 and 0.75 quantiles; in contrast, the effect of high quantiles of stock market returns is positive on the housing market.

It seems that the demand in the housing market increase in a situation where the returns of the stock market are growing, and the market is in a bullish condition, and this causes an increase in the price and returns in this market. In addition, the results show that the effect of stock market returns on capital market returns is asymmetric and nonlinear.

The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously.

The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board.

The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods.

This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship.

The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon.

Kapok was well-known for its oleophilic properties, but its mechanical properties and morphology impeded it from forming suitable absorbent materials. This study aims to demonstrate the process of creating an oil-absorbent web from a blend of treated kapok and polypropylene fibers.

Kapok fibers were separated from dried fruits, then the wax was removed with an HCl solution at different concentrations. The morphological and structural changes of these fibers were investigated using scanning electron microscopy images. The blending ratios of kapok and polypropylene fibers were 60/40, 70/30 and 80/20, respectively. The fiber blends were fed to a laboratory carding machine to form a web and then consolidated using the heat press technique. The absorption behavior of the formed web was evaluated regarding oil absorption capacity and oil retention capacity according to ASTM 726.

The results showed that the HCl concentration of 1.0% (wt%) gave the highest wax removal efficiency without damaging the kapok fibers. This study found that oil absorbency is influenced by the fiber blending ratio, web tensile strength and elongation, porosity, oil type and environmental conditions. The oil-absorbency of the web can be re-used for at least 20 cycles.

This study only looked at three types of oils: diesel, kerosene and vegetable oils.

When the problem of oil spills in rivers and seas is growing and causing serious environmental and economic consequences, using physical methods to recover oil spills is the most effective solution.

This research adds to the possibility of using kapok fiber in the form of a web of non-woven fabric for practical purposes.

Purpose of This Chapter: This research aims to study the need for more age of qualified talent. The evolving corporate needs, education, and curriculum require urgent reform. Current university methods do not align with corporate demands due to outdated content and ineffective pedagogy.

Design / Methodology / Approach: Drawing on established research, this study delves into 7 prominent training strategies across 14 sectors. A survey of 53 HR professionals and managers forms the basis for employing the non-linear best–worst method (BWM) and the Fuzzy BWM to discern the most effective training and development (T&D) modules. This comprehensive methodology ensures a nuanced analysis of T&D practices and insights for businesses seeking to align with Industry 5.0 demands.

Findings: On-the-job training emerges as the most impactful method, followed by case studies, interactive group learning, and more. These methods enhance employee skills in Industry 5.0.

Research Limitations: Limited by a small sample, future research should expand participant diversity for robustness.

Practical Implications: The study holds significance for bridging the skill gap between academic institutions and Industry 5.0. Aligning strategies with industry needs reduces skill disparities, fuels growth, and addresses employability. The study’s impact extends to society, lowering unemployment and shaping a resilient, adaptable workforce for Industry 5.0.

Originality: This innovative research examines decision-making for implementing T&D strategies in the emergence of Industry 5.0, aligning with a human-centric approach to business transformation.

The present work aimed to present the perception of Tunisian professionals towards companies engaged in social responsibility practices and describe the tax evasion strategies of socially responsible Tunisian companies following the coronavirus disease 2019 (COVID-19) pandemic (COVID-19) shock.

A survey was sent to 119 Tunisian tax administration auditors. Data analysis methods principal component analysis (PCA) and regression analysis were used. The data were collected through a questionnaire after the general containment of Tunisia from September 2020 to February 2021. These quantitative data were analysed using processing software (STATA).

Professionals of the tax authorities, particularly those in charge of the audit mission, aim for corporate profitability from the perspective of stakeholders that seek to integrate ethics and social responsibility into companies and consider employee morale a top priority. The results show that highly ethical and socially responsible professionals are far from practising aggressive strategies. Thus, an auditor from the tax administration is far from engaging in social responsibility to justify fraudulent acts. During the COVID-19 period, the role of these professionals was to prevent and detect fraud in the tax sector to fight corruption and investigate taxes based on sound regulations.

The results are consistent with optimal taxation theory, which postulates that a tax system should be chosen to maximise a social welfare function subject to a set of constraints. Professionals seek to make taxation much simpler for taxpayers by providing advice and consultation to manage tax obligations. The minimisation of tax or the play of tax values requires expertise in the field to respect legal constraints. Therefore, these professionals play a crucial role in tax collection, as the professionals' advice and suggestions can influence taxpayers' decision-making.

In recent years, academic researchers, policy makers and the public have become increasingly interested in corporate tax evasion behaviour. At the same time, companies are under increasing pressure to integrate CSR into the companies' decision-making processes, which has led to increased academic interest in CSR. Opportunistic tax minimisation reduces state resources and funds needed for government programmes to improve the social welfare of the entire community. This study represents an overriding concern not only for legal and tax authorities and companies, but also for shareholders and stakeholders.

The authors' study contributes to the existing literature by determining the state of play on corporate social responsibility (CSR) practices amongst Tunisian tax authorities' professionals. In Tunisia, an executive of the tax authorities in charge of the verification mission is required to verify the proper application of the accounting and tax legislation in force, follow up on tax control operations on declared taxes and validate the sincerity of the accounts. This study focussed on the tax evasion of companies engaged in social responsibility practices according to the judgements of Tunisian tax authorities' auditors during the global COVID-19 pandemic.

Food is a key element in tourism experiences. This study aims to investigate the interplay of sensory and non-sensory factors in food tourism experiences and models their influence on satisfaction and behavioural intentions.

The study focuses on the culinary experiences of 304 tourists dining at ethnic restaurants and uses causal relationship discovery modelling to analyse data.

Sensory factors are important in tourists’ culinary experiences with cleanliness, noise levels and room temperature at the top of the causal chain. Results also indicate the interplay between sensory and non-sensory factors to explain overall satisfaction, intention to return and intention to say positive things.

Using embodied cognition theory, the study offers novel insights into the role of senses in food tourism experiences at rural destinations.

美食是乡村旅游的主要吸引物之一。本研究的目的是调查游客在用餐体验中感官和非感官因素的相互作用, 以及这些因素如何影响游客的满意度和行为意愿。

本研究使用因果关系建模的方法来分析 304 名在某地方特色餐厅用餐的游客的问卷数据。

结果显示, 对于游客的用餐体验而言, 感官和非感官因素具备同等的重要性。此外, 结果发现, 游客感知到的噪音水平、适宜的室内温度及清洁度在与其他因素的相互作用中非常重要, 并能激发游客的满意度和重游意愿。

基于认知理论, 本研究为更好地理解感官因素和非感观因素在乡村旅游情境下的游客用餐体验中的作用提供了新的知识。

La comida es un elemento clave en las experiencias turísticas. Este estudio investiga la interacción de factores sensoriales y no sensoriales en las experiencias de turismo gastronómico y modela su influencia en la satisfacción y las intenciones de comportamiento.

El estudio se centra en las experiencias culinarias de 304 turistas que cenan en restaurantes étnicos y utiliza modelos de descubrimiento de relaciones causales para analizar los datos.

Los factores sensoriales son importantes en las experiencias culinarias de los turistas con la limpieza, los niveles de ruido y la temperatura ambiente en la parte superior de la cadena causal. Los resultados también indican la interacción entre factores sensoriales y no sensoriales para explicar la satisfacción general, la intención de regresar y la intención de decir cosas positivas.

Utilizando la teoría de la cognición incorporada, el estudio ofrece nuevos conocimientos sobre el papel de los sentidos en las experiencias de turismo gastronómico en destinos rurales.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

Brief introduction on the importance and the need for plastic analysis methods were presented in the beginning section of this review. The plastic method for analysis was considered to be the more advanced method of analysis because of its ability to represent the true behaviour of the steel structures. Then in the following section, a literature analysis has been carried out on the previous investigations done on steel plates, steel beams and steel frames by other authors. The behaviour of them under different types of loading were presented and are under the investigation of innovative new analysis methods.

Structure member connections also have the potential for plastic failure. In this study, the authors have highlighted a few topics to be discussed. The three topics in this study are T-end plate connections to a square hollow section, semi-rigid connections and cold-formed steel storage racks with spine bracings using speed-lock connections. Connection is one of the important parts of a structure that ensures the integrity of the structure. Finally, in this technical paper, the authors introduce some topics related to seismic action. Application of the Theory of Plastic Mechanism Control in seismic design is studied in the beginning. At the end, its in-depth application for moment resisting frames-eccentrically braced frames dual systems is investigated.

When this study involves the design of a plastic structure, the design criteria must involve the ultimate load rather than the yield stress. As the steel behaves in the plastic range, it means the capacity of the steel has reached the ultimate load. Ultimate load design and load factor design are the methods in the range of plastic analysis. After the steel capacity has reached beyond the yield stress, it fulfills the requirement in this method. The plastic analysis method offers a consistent and logical approach to structural analysis. It provides an economical solution in terms of steel weight, as the sections designed using this method are smaller compared with elastic design methods.

The plastic method is the primary approach used in the analysis and design of statically indeterminate frame structures.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.