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This research examines the influence of the digital voice of consumers (DVoC) on the resilience of supply chains (SCR) within the renewable energy sector. The main goal is to identify and highlight the crucial aspects that enable the examination of this impact.

A comprehensive literature analysis was performed utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach to ascertain pertinent factors. This research utilizes a comprehensive methodology that merges interpretive structural modeling (ISM) with Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis to assess the discovered variables.

The study identified 16 factors that contribute to both DVoC and SCR. Key influential factors include top management support, collaboration, feedback influence and flexibility. These factors play a significant role in enhancing SCR by facilitating better adaptation and response to disruptions.

The study is confined to the renewable energy sector and may lack generalizability to other businesses without additional validation. Subsequent studies ought to investigate the implementation of these findings across various industrial contexts to enhance comprehension of DVoC’s influence on SCR.

This study presents a new integrated framework for comprehending the function of DVoC in improving SCR. It presents significant practical consequences for stakeholders in the renewable energy sector, such as researchers, regulators, manufacturers and consumers, highlighting the necessity for a resilient and flexible supply chain.

The objective of this study is to accurately predict the cost of green buildings to provide quantifiable criteria for investment decisions from investors.

This study proposes a hybrid prediction model ML-based for cost prediction of GBPs and obtains prediction parameters (PPs) associated with project characteristics through data mining (DM) techniques. The model integrates a principal component analysis (PCA) method to perform parameter dimensionality reduction (PDR) on a large number of raw variables to provide independent characteristic terms. Moreover, the support vector machine (SVM) algorithm is improved to optimize the prediction results and integrated with parameter dimensionality reduction and cost prediction.

The prediction results show that the mean absolute and relative errors of the hybrid prediction model proposed in this study are equal to 39.78 and 0.02, respectively, which are much lower than those of the traditional SVM model and MRA prediction model. Moreover, the hybrid prediction model with parameter dimensionality reduction also achieved better prediction accuracy (R² = 0.319) and superior prediction accuracy for different cost terms.

Theoretically, the hybrid prediction model developed in this study can reliably predict the cost while accurately capturing the characteristics of GBPs, which is a bold attempt at a comprehensive approach. Practically, this study provides developers with a new ML-based prediction model that is capable of capturing the costs of projects with ambiguous definitions and complex characteristics.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

Legitimacy is the perceived appropriateness of an organisation to a social system in terms of values, norms and definitions. This research analyses how customer reviews, news media and experts’ opinions influence the legitimacy perception of high-end restaurants. The aim is to understand how collective evaluators’ opinions impact the individual legitimacy perception, linking the micro and macro levels of legitimacy. This study measures and analyses the relationships and impacts of individual (customers) and collective (experts and news media) judgments to rationalise these differences in legitimacy perceptions.

This research was conducted through a combined analysis of the reviews published in news media, online customer review platforms and experts’ publications. This study elaborates a theoretical model using partial least squares structural equation modelling analysing 246 Michelin-starred restaurants in Spain.

Our findings indicate that individual legitimacy judgments are impacted by news media but not by experts. On the contrary, experts’ evaluations positively impact news media’s evaluations. The individual legitimacy perception of the Haute Cuisine restaurant is influenced by the collective judgments of news media.

The novelty of this research states the application of the multi-level legitimacy theory to analyse the relationship between news media, online customer reviews and expert evaluations, thus the individual and collective legitimacy perceptions of Haute Cuisine restaurants. Additionally, this study adds to legitimacy theory by revealing the relationships of legitimacy judgments on micro and macro levels and analysing which and how audiences perceive organisational legitimacy.

The purpose of this paper is to characterize a new structural bi-material (scaffold and filler).

The bi-material has been obtained by means of an additive manufacturing system consisting of a fused filament fabrication extruder head and an epoxy resin depositor head. The new bi-material will consist of a thermoplastic material that will serve as the main structure and an epoxy resin that will serve as a filler and adhesion between layers. The creation of this new bi-material will improve the physical–chemical and mechanical properties with respect to the thermoplastic material. This paper will focus on the impact behavior of IZOD and the impact behavior of punctures.

The new polylactic acid (PLA) and epoxy bi-material allow improvements in toughness and puncture impact resistance compared to the PLA thermoplastic. This increase in toughness is between 20% and 30% depending on the orientation of the print. In the same way, the energy absorbed in the puncture impact test has been increased by 42%–48%.

The improvement in the impact absorption capacity of this new bi-material makes it ideal for the manufacture of medical parts in which customization, lightness and impact resistance are their main characteristics such as sports protection systems.

The originality of creating parts through additive manufacturing that combines a material generated with cold extrusion, such as epoxy resin and a material generated with hot extrusion, such as thermoplastics, lies in the unique synergy that this mixed and simultaneous technique offers. By uniting these two manufacturing methods, it allows the exploration of new physical and chemical properties in the resulting parts, taking advantage of the individual advantages of each material. This combination opens the door to the creation of components with a wider range of characteristics, from strength and durability to flexibility and temperature resistance, thus offering innovative and versatile solutions for various applications in fields such as engineering, medicine and design.

In this paper, the theory of inequality of opportunity is applied to examine health inequality among adults in Spain. Using a survey module conducted by the Centro de Investigaciones Sociológicas (CIS) in 2017, the role played by and the contributions of circumstances, efforts and lifestyles, and demographic variables in explaining adult health inequality are assessed. Additionally, the mediating role of individual education in the relationship between circumstances and health is analyzed. The findings underscore the significant relevance of unfair factors (circumstances) and demographics in generating adult health inequality, as opposed to the minimal contribution of fair factors (efforts and lifestyles). Furthermore, education is shown to significantly influence health, mitigating the impact of certain circumstances and serving as a transmission channel for others. In light of these results, efforts and lifestyles alone are insufficient to counterbalance unfair circumstances beyond an individual’s control. Therefore, improving circumstances and early-life factors, or reducing their impact on health through the implementation of compensatory policies, is essential for reducing health inequality and promoting equal opportunities for inclusive development.

In this study the effect of the level of economic development on inequality is estimated. The goal is to determine whether the classical Kuznets curve hypothesis (1955) is applicable to Russia. The idea of Kuznets was that income inequality first rises with economic growth on the low stages of development and then falls as the economy matures. The empirical evidence of the curve applicable for the Russian regions has been found. The reverse casualty problem by using internal and external instruments has been also taken into the consideration. For the internal instruments, the System GMM method, which implies two functions – one in first difference and the other one in levels, has been used. For the external instruments, the net oil export per capita and trade per capita as instruments have been applied. If the quadratic term is not implied, the estimations show a significant robust positive effect of economic development on inequality. Thus, it is assumed that it happens due to the fact that Russia is still on the first upbeat of the curve, and it has not yet reached sufficient levels of development to tear down inequality.

This paper aims to reveal the green governance role played by stock connect in transition economies from the perspective of corporates’ environmental violations and provides implications for the coordination and optimization of subsequent stock market liberalization and green transformation policies in pursuit of carbon peaking and carbon neutrality goals.

With the data of Chinese listed enterprises, this paper takes the Shanghai-Hong Kong Stock Connect or Shenzhen-Hong Kong Stock Connect in China as a quasi-natural experiment and applies the multi-period difference-in-difference (DID) model to identify the impact of stock market liberalization on the corporates’ environmental violations.

The findings reveal that the stock market liberalization significantly restrains the corporates’ environmental violations. These findings are robust to a series of sensitivity tests, including excluding two-way effects, adjusting the year of policy implementation, replacing the core variables, introducing the regional fixed effects and excluding the interference effect of other relevant policies during the sample period. Furthermore, the stock market liberalization is beneficial for upgrading information disclosure quality, improving internal governance capability, strengthening environmental protection incentives, and thus restrains corporates’ environmental violations. Meanwhile, heterogeneity tests show that the inhibitory effects are more significant in those grouped samples which is large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden.

We make two marginal contributions to the current literature. First, this paper enriches the literature on the factors influencing corporate environmental violations by focusing on how the macro-level financial policy influences the micro-level corporate environmental violations. One the one hand, prior studies mainly focused on the consequences of corporate environmental violations; however, there is still a puzzle that the effect of stock market liberalization cannot be fully justified to influence corporate environmental violations. The findings help explain this puzzle by examining that stock market liberalization can restrain corporate environmental violations. Moreover, prior studies mainly focused on corporate share price (Yunsen Chen et al., 2022), market liquidity (Han Kim and Singal, 2000), information disclosure (Liang, Lin, and Chin 2012), corporate governance (Bae and Goyal, 2010) and corporate violations (Lingyun Xiong et al., 2021), but not on corporate environmental violations. We assume that the suppression effect of stock market liberalization on corporate environmental violations can help reduce corporate environmental violations, improve corporates’ awareness of environmental compliance. Second, this paper contributes to a better understanding of the literature on stock market liberalization by investigating the restraining effect of Stock Connect on corporate environmental violations from the perspective of information channel, corporate governance channel and motivation channel, which is of practical significance. Moreover, we investigate the differences in the inhibitory effects of stock market liberalization on different enterprises' environmental violations, from firm size, property rights, enterprise assessment results, tax burden to geographical location, which is conducive to the construction of a green financial system and the promotion of sustainable economic development. Our results show that firms which are large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden tend to compliance with environmental laws. These findings emphasize the importance and benefits of Stock Connect.

Retail omnichannel implementation faces barriers hindering accurate and efficient integration across marketing channels. Our desk examination identified a need for a broader perspective in investigating these barriers, moving away from a dominant, narrow approach. This research aims to develop a comprehensive set of items to measure retail omnichannel obstacles, refine the scale and assess its reliability and validity for a robust measurement tool.

Our approach combines quantitative and qualitative methods, using data from primary and secondary sources to create and validate the omnichannel obstacles scale.

This study emphasises the inclusive nature of retail functional areas, departing from prior literature that examined them in isolation. Instead of focussing on separate domains where retail omnichannel obstacles may arise, we adopt a holistic perspective by integrating previously disconnected elements.

We assert that challenges in retail omnichannel operations encompass three distinct dimensions: operational efficiency, channel inefficiency, and strategy and organisational culture within retailing. In our final validated measurement model, we consolidate the channel inefficiency dimension and refine the omnichannel obstacles scale to emphasise two areas of consideration.

This study aims to analyze the entrepreneurial intention (EI) of Colombian researchers using machine learning (ML) techniques, considering their academic activity, contexts and social norms (SN).

Unsupervised classification techniques were applied, including principal component analysis, hierarchical clustering with the Ward method and a logistic model to evaluate the classification. This was done to group researchers according to their characteristics and EI.

The methodology used allowed the identification of three groups of academics with distinct characteristics, of which two showed a high presence of EI. The results indicate that EI is influenced by the connection with the private sector (consulting, intellectual property and applied research) and by the lack of institutional support from universities. Regarding SN, only the preference for entrepreneurial activity over being an employee and the social appreciation of entrepreneurial dedication were identified as predictors of EI.

The use of ML techniques to study the EI of researchers is uncommon. This study highlights the ability of the methodology used to identify differences between two groups of academics with similar characteristics but different levels of EI. One group was identified that, despite rejecting values associated with entrepreneurs, has a high predisposition to develop a career as an entrepreneur. This provides valuable information for designing policies that promote EI among Colombian researchers.