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This study aims to demonstrate a modified wire arc additive manufacturing (AM) named non-transferring arc and wire AM (NTA-WAM). Here, the build plate has no electrical arc attachment, and the system’s arc is ignited between tungsten electrode and filler wire.

The effect of various deposition conditions (welding voltage, travel speed and wire feed speed [WFS]) on bead characteristics is studied through response surface methodology (RSM). Under optimum deposition condition, a single-bead and thin-layered part is fabricated and subjected to microstructural, tensile testing and X-ray diffraction study. Moreover, bulk texture analysis has been carried out to illustrate the effect of thermal cycles and tensile-induced deformations on fibre texture evolutions.

RSM illustrates WFS as a crucial deposition parameter that suitably monitors bead width, height, penetration depth, dilution, contact angle and microhardness. The ferritic (acicular and polygonal) and lath bainitic microstructure is transformed into ferrite and pearlitic micrographs with increasing deposition layers. It is attributed to a reduced cooling rate with increased depositions. Mechanical testing exhibits high tensile strength and ductility, which is primarily due to compressive residual stress and lattice strain development. In deposits, ϒ-fibre evolution is more resilient due to the continuous recrystallisation process after each successive deposition. Tensile-induced deformation mostly favours ζ and ε-fibre development due to high strain accumulations.

This modified electrode arrangement in NTA-WAM suitably reduces spatter and bead height deviation. Low penetration depth and dilution denote a reduction in heat input that enhances the cooling rate.

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.

The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.

The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.

Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.

This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.

This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.

To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.

The purpose of this study is to fill the research gap by investigating the impact of brand social initiatives on both the warmth and competence dimensions of the brand, as well as examining the brand's potential to induce pro-environmental behavioral change among consumers.

The study employed a scenario-based survey design and surveyed 415 consumers in India. The data were analyzed using structural equation modeling (SEM) with SmartPLS 4.0.

The results show that social initiatives enhance both dimensions of social perception and increase cooperative intentions. Brand competence is more crucial than warmth in predicting behavioral intentions. Brand-cause fit, CSR commitment and initiatives' impact all influence the brand image. A brand's commitment to the cause is more significant than brand-cause fit in determining how consumers evaluate a brand.

This research provides insights into how social initiatives can enhance brand image and encourage helping intentions through effective communication traits. It can aid brands in building consumer trust, benefiting society and boosting finances. The study offers a framework for effective cause communication strategies, highlighting the importance of commitment to the cause over fitting with the brand's image to elicit desired responses.

This study is a novel attempt that uses the stereotype content model and costly signaling theory to explore how social initiatives influence a brand's warmth and competence and impact consumer behavior. It provides critical insights into the psychological mechanisms behind social initiatives' impact on consumer behavioral intentions.

Since the outbreak of the COVID-19 pandemic, the demand for online services has risen, with e-payment emerging as a prominent option for customers seeking faster and more convenient transactions to complete their online purchases. Nevertheless, e-payment adoption in Egypt remains a challenge that requires further investigation. Thus, this study aims to investigate the factors influencing online customers’ attitudes and intentions towards adopting e-payment for online transactions, social influence, perceived ease of use, perceived usefulness, perceived trust, structural assurance and perceived privacy/security risk.

The data were gathered from 302 customers in Egypt and structurally analysed based on partial least squares structural equation modelling (PLS-SEM).

The findings revealed that social influence, perceived usefulness and perceived trust are significant antecedents of attitude. Furthermore, perceived usefulness, perceived trust, perceived privacy/security risk and attitude directly influence behavioural intention. Structural assurance and perceived trust directly influence perceived privacy/security risk. Moreover, perceived usefulness, perceived trust and attitude were found to have several mediating roles.

This study adds new empirical evidence from a developing country regarding the adoption of e-payment among online customers. In addition, its findings can help the government, practitioners and policymakers understand how to promote customers’ positive attitudes and encourage their intentions towards using e-payment.

The findings of this study can contribute to the digital transformation strategy in Egypt by providing insights into enhancing online shoppers’ attitudes and intentions towards e-payment adoption. This, in turn, can boost Egyptian e-commerce and the country's digital economy as a whole.