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We investigate the interconnectedness between the financial sectors and new energy companies in China from the perspective of the multilayer network, and analyze the static and time-varying characteristics of the multilayer network at system and company levels, respectively.

We employ the multilayer network containing the realized volatility (RV here after) layer, the realized skewness (RS here after) layer and the realized kurtosis (RK here after) layer. The three realized indicators adopted to construct the multilayer network are generated by the intraday trading data from 2012 to 2022.

(1) Different layers have different characteristics, and can provide supplementary information. (2) Banks tend to play the role of risk transmitters on the whole, while the insurances and new energy companies tend to play the role of risk receivers on average. (3) The connectedness strength of financial sectors and new energy companies varies over time, and climbs sharply during the major crisis events. The roles of financial sectors and new energy companies may change from risk transmitters to risk receivers, and vice versa.

We adopt three realized indicators to construct the three-layer network, which provides a more comprehensive perspective for understanding the connectedness between the financial sectors and new energy companies in China.

Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.

This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.

The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

The study aims to investigate consumer preferences across 25 attributes of plant-based milk (PBM) products and examine the key predictors and underlying mechanisms of consumer purchase decisions of PBM alternatives.

This study employed a multidimensional approach to investigate consumer preferences and the determinants of PBM purchasing decisions. Drawing on data from 819 online surveys conducted in the Jing-Jin-Ji region of China in 2021, we measured consumer preferences across 25 specific attributes and other individual characteristics. Purchasing decisions were framed as a two-stage process – the decision to purchase (frequency) and the decision on how much to pay (WTP). The Least Absolute Shrinkage and Selection Operator (LASSO) model was utilized to examine these dimensions separately, and the selected predictors were incorporated into OLS linear and Heckman’s two-stage regression analyses to establish the underlying mechanisms.

The findings indicate that consumers exhibit a strong preference for freshness and the absence of spoilage, followed by taste experiences such as taste and aroma. Preferences for milk preservation significantly increase the purchase frequency of PBM, while preference for calorie content has a negative and significant impact. Preferences for milk preservation, aroma and processing methods can also significantly increase WTP. Preferences vary across PBM categories. Social influence, knowledge and advertising exposure positively impact purchase frequency and WTP. Consumers with low food neophobia tend to be more responsive to product-related factors, such as freshness, calorie content and processing methods, in their purchase decisions.

This study contributes to the extant literature by comprehensively examining the determinants of consumer purchase decisions for PBM alternatives. The findings provide practical implications for marketers and policymakers, highlighting the strategic product attributes, consumer segments and marketing levers that can effectively target and cater to consumer preferences for PBM alternatives.

Due to ginger holds a special and indispensable place in Chinese cuisine, understanding consumers’ preferences for organic ginger is of significance, especially given the growing interest in organic food products and sustainable agriculture. This study thus examines Chinese consumers’ preference for fresh ginger and the sources of their preferences heterogeneity for organic ginger consumption.

The study is using choice experiment (CE) method and mixed logit (MXL) modeling with 1,312 valid samples. The participants are regular consumers who are 18 years old or above and had bought fresh ginger within the past 12 months.

The results show that consumers prefer organic product certification labeling ginger to conventional ginger, preferred to purchase ginger at wet markets to at supermarkets or online, and preferred either ginger with regional public brand or private brand to unbranded ginger. Results also indicate that age, education level, income, purchasing experience of organic and branded ginger, and cognition of ginger health benefits are the sources of heterogeneity in consumer preferences for organic ginger.

This study contributes to ginger growers, marketers and policy makers. This study tracks how consumers' preferences change under different attribute combinations, capture the complex preference structure of consumers, and help reveal the motivations behind consumers' preferences for organic ginger. These findings will be crucial for developing marketing strategies, promoting organic products, and meeting consumer needs.

Audit consortium of joint and dual audits is one of the most controversial mechanisms aimed at improving audit quality and resolving several related debatable issues. This study aims to empirically investigate the impact of audit consortium on audit quality assessment in Egypt. It specifically examines whether audit opinion modification level is triggered by joint and dual audits existence and whether it is influenced by the relative importance of the auditor pair combination types.

A sample of companies listed on the Egyptian Stock Exchange constituting the EGX 30 index is examined over a period of five years, from 2016 to 2020. A quantitative research methodology is used, using content analysis of companies’ audit reports and carrying out longitudinal panel ordinary least squares multiple regression tests.

Results show that audit quality is significantly enhanced by conducting joint and dual audits of Egyptian companies’ financial statements. Findings indicate that both joint and dual audits significantly increase auditors’ propensity to modify audit opinions as compared to companies that engage in single audits. However, this increase in audit quality is not supported by the presence of Big 4 joint auditors or affiliated joint auditors, while the impact of Big 4 dual auditors cannot be confirmed. Nevertheless, such a potential increase in audit opinion modification is boosted by the presence of affiliated dual auditors, which appears to translate into higher quality.

The study has important implications for researchers, corporates, those charged with governance, financial statement users, auditors, regulators and standard setters, who might be interested in whether an audit consortium and a particular auditor pair combination are associated with superior audit quality. It provides empirical evidence that might contribute to the continuous challenge of promoting the quality and effectiveness of the external audit.

This study adds to the relatively limited and challenging literature on the potential contribution of audit consortium, using audit opinion modification level as a direct assessment of audit quality. It extends the scope of prior research by examining the existence of joint and dual audits and the relative importance of joint and dual auditor pair combination types. The study provides key insights from a distinctive and complex emerging audit market.