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The purpose of this paper is to investigate the free vibration response of a laminated honeycomb sandwich panels (LHSP) for aerospace applications. Higher order shear deformation theory (HSDT) was simplified for the dynamic analysis of LHSP. Furthermore, the effects of honeycomb parameters on the value of natural frequency (NF) of vibration were explored.

This paper applies HSDT to the analysis of composite LHSP to derive four vibration differential equations of motion and solve it to find the NF of vibration. Two analytical models (Nayak and Meunier models) were selected from literature for comparison of the NF of vibration. In addition, a numerical model was built by using ABAQUS and the results were compared. Furthermore, parametric studies were conducted to explore the effect of honeycomb parameters on the value of the NF of vibration.

The present model is successful in simplifying HSDT for the analysis of LHSP. The first five natural frequencies of vibration were calculated analytically and numerically. In the parametric study, increasing core height or young’s modulus or changing laminate layup will increase the value of NF of vibration. Furthermore, increasing plate constraint (using clamped edge boundary condition) will increase the value of NF of vibrations.

The current analysis is suitable for all-composite symmetric LHSP. However, for isotropic or non-symmetric materials, minor modifications might be adopted.

The application of simplified HSDT to the analysis of LHSP is one of the important values of this research. The other is the successful and complete dynamic analysis of all-composite LHSP.

This chapter is one of five chapters dedicated to anti-racism, specifically focusing on its conceptual foundations. Drawing from critical scholarship on ideas that have inspired political debates and policies about racism, I address key questions pertaining to anti-racism as an idea, policy framework and as a catalyst for sociopolitical action. This chapter engages with the fundamental principles that underpin anti-racism endeavours, ranging from community engagement to political activism and civil rights movements. It critically examines the ongoing debates on whether the goals of anti-racism, such as racial justice and dismantling of institutional racism/privilege, align with existing sociopolitical order. In addition, this chapter contributes to anti-racism scholarship that has evolved over the past five decades, by synthesising how anti-racism relates to various societal goals. Furthermore, this discussion incorporates themes such as the promotion of tolerance, equality, social justice and recognition within the context of anti-racism.

The purpose of this study is to assess the influence of institutional quality (IQ), fossil fuel efficiency, structural change and renewable energy (RE) consumption on carbon efficiency.

This research uses an econometric approach, more specifically the Autoregressive Distributed Lag model, to examine the relationship between structural change, RE consumption, IQ, fossil fuel efficiency and carbon efficiency in India from 1996 to 2019.

This study finds the positive contributions of variables like fossil fuel efficiency, technological advancement, structural transformation, IQ and increased RE consumption in fostering environmental development through enhanced carbon efficiency. Conversely, this study emphasises the negative contribution of trade openness on carbon efficiency. These findings provide concise insights into the dynamics of factors impacting carbon efficiency in India.

This study's exclusive focus on India limits the generalizability of findings. Future studies should include a broader range of variables impacting various nations' carbon efficiency. Furthermore, it is worth noting that this study examines renewable and fossil fuel efficiency aggregated. Future research endeavours could yield more specific policy insights by conducting analyses at a disaggregated level, considering individual energy sources such as wind, solar, coal and oil. Understanding how the efficiency of each energy source influences carbon efficiency could lead to more targeted and practical policy recommendations.

To the best of the authors’ knowledge, this study addresses a significant gap in the existing literature by being the first empirical investigation into the effects of IQ, fossil fuel efficiency, structural change and RE consumption on carbon efficiency. Unlike prior research, the authors consider a comprehensive IQ index, providing a more holistic perspective. The use of a comprehensive composite index for IQ, coupled with the focus on fossil fuel efficiency and structural change, distinguishes this study from previous research, contributing valuable insights into the intricate dynamics shaping India's path towards enhanced carbon efficiency, an area relatively underexplored in the existing literature.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

The purpose of this study is to examine the impact of fashion influencer measures on consumers' purchase intentions and the mediation of attitudes to understand the phenomenon of influencer marketing in the backdrop of the fashion industry.

The present study employs a conceptual model based on extended theory of planned behaviour (TPB) with added perceived trust. Data were collected from 341 participants from different regions of the country and analysed using direct path analysis and mediation technique.

The study found that attitudes toward fashion influencers are positively influenced by perceived trust, subjective norms and perceived behavioural control. However, perceived behavioural control is not directly related to purchasing intents in the research model. The results confirmed that attitudes have a positive association with purchase intentions both directly and indirectly (partially mediation).

The study advocates market practitioners and advertisers to acknowledge the increasing importance of influencer marketing and the promotion of their fashion offerings in the setting of emerging fashion industry.

The present study adds crucial value to enhance the understanding of fashion influencer marketing in the Indian context. This research offers several insights into the continually growing knowledge domain of influencer marketing by predicting the direct relationships with purchase intents and the mediation of attitudes.

This study aims to determine the solutions to address the Indian attitude-behaviour inconsistency in the green purchasing context and provide the possible combinations of antecedents that aid Indian marketers in designing promotional and advertising strategies.

A non-probability criterion-based sampling technique was used in collecting the data across Hyderabad city of Telangana region through online survey technique. The respondents were the customers who were attracted towards green and eco-friendly products. A total of 129 responses were received. SPSS v26 software was used to conduct the descriptive analysis, and the two-step analysis approach of the measurement and structural model was conducted in SmartPLS.

Results indicate that interpersonal influence has a greater direct influence on green purchase behaviour (GPB); altruism’s influence on green purchase intention (GPI) and GPB is through environmental attitude (EA) and green awareness (GA). EA has a significant influence on GA and green behaviour (GB). The GA and GB individually act as potential mediators between EA and green consumption behaviour (GCB) variables. Perceived environmental knowledge (PEK) does not influence GPB directly or indirectly. Altruism still ranks at the fifth position among the six antecedents, indicating reciprocal determinism and not an altruistic purchase approach in the Telangana region.

The results of this study may be used by government agencies and policymakers to launch awareness campaigns aimed at educating the public and encouraging green buying practices among broader societal segments. These kinds of programmes could lessen the harm that inconsiderate consumption habits do to the environment and to society, increase the green behaviour practices like planting trees, and recycling, and also increase the consumer’s PEK.

To the best of the authors’ knowledge, the present study is the first to apply reciprocal deterministic theory along with theory of planned behaviour to predict Indian GCB and address the attitude-behaviour gap. Moreover, to the best of the authors’ knowledge, this is the first study to investigate together the direct and indirect influence of altruism, interpersonal influence and perceived environmental knowledge on green purchase behaviour. Given the growing trend of consumers adopting an eco-friendly mind-set, a novel approach to empirically discuss the behavioural and personal factors will give research the much-needed boost it needs.

This chapter addresses the question of what normatively binding claims can be associated with the principle of sustainability. It proposes a theoretical reading of justice that requires a new level of morality, namely a global (spatial), intergenerational (temporal) and ecological (material) extension of the scope of responsibility. This makes it plausible that responsibility for those who are distant in space and time, as well as for nature, becomes a matter of conscience. At the same time, it is shown how the binding claims resulting from the principle of sustainability can be internalised in the course of a conscience formation and how the gap between knowledge and action in questions of sustainable development can be closed by means of an emotional underpinning. Finally, it is proposed to transfer the question of conscience to spatial units and tourism through the model of ‘Destination Conscience’ and to institutionalise the idea of ‘inner commitment’ or self-commitment. One suggestion is the creation of committees that could be a collective ethical conscience for the future issues.

The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.

A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.

The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.

In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.

After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.

The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.

This study in Iran examined the role of internal and external psychological factors that affected green purchase intention. Moreover, it examined these variables' direct and indirect effects and green purchase intention on green purchase behavior.

An extended version of the theory of planned behavior (TPB) was employed, based on which a theoretical model was designed to reach the authors’ aim. An online questionnaire was used to collect data. For data analysis, confirmatory factor analysis, structural equation modeling, the bootstrapping method and the Preschool Language Scale (PLS) product-indicator approach were conducted to test the proposed conceptual model.

Results show that self-identity, self-interest, self-efficacy and a growth mindset have a positive impact on green purchase intention. However, the study found no predictive effect from peer influence and warm glow. In addition, self-efficacy and green purchase intention significantly affect green purchase behavior. The study reveals that green purchase intention substantially mediates the relationship between self-interest, growth mindset, warm glow and green purchase behavior. Further, warm glow moderates the impact of peer influence, self-identity and self-efficacy on green purchase intention. This study emphasizes the critical role of dispositional factors on green purchase intention and behavior.

Few studies consider the effect of the individual self, a growth mindset, a warm glow and peer influence on green purchase intention simultaneously. In addition, the authors introduced a different version of the TPB model. Further, this research also conducted how these variables, directly and indirectly, affect green purchase behavior.

This research aims to determine the influence of environmental, social and governance (ESG) factors on market performance. The study shows the perspective of ESG on market performance. The study attempted to test the relationship between ESG and Tobin’s Q and the effect of control variables.

The study used panel data from a sample covering 720 firms and ran a fixed-effects model regression during the 2007–2019 period for eight European countries’ listed companies.

The findings reveal that ESG positively impacts Tobin’s Q. According to the findings, high company ESG performance boosts market performance via the moderator effect of competitive advantage. The results indicate that all control variables are significant. The firm’s leverage has a negative relationship with ESG. The size of the firm impacts ESG positively. Also, the results prove that the firm’s size and industry positively affect Tobin’s Q.

The findings of this study suggest that managers, practitioners and authorities interested in learning about ESG scores (ESGSs), market performance and competitive advantage might draw intriguing conclusions from the data. Managers can identify the appropriate levels of competitive advantage that improve market performance. Practitioners must determine whether fit, size, growth, leverage and industry could enhance market performance. The findings also give authorities and the board of directors information on future growth opportunities for the company and the country.

The research presents a vision of how ESG factors affect market performance. This study aims to identify the positive link between ESGSs and European market performance.