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This study is based on the extended theory of planned behavior (TPB) and attempts to shed light on what influences restaurant consumers’ intentions to eat locally sourced meals.

Data from 698 respondents were gathered through a web-based survey employing a quantitative methodology.

The findings indicated that several motivating factors, subjective norms and perceived behavioral control positively influence respondents’ attitudes toward dining at restaurants serving meals that are obtained locally. Also, attitudes significantly predicted intentions and mediated the relationship between the motivating factors and intention to consume local meals. Furthermore, subjective norms and perceived behavioral control moderated the relationship between attitude and intention.

The study offers implications for both theory and practice. In the context of Egypt in particular, this study advocates for sustainable food production and consumption in restaurants. The study focused only on consumers; it suggests that subsequent research should examine the restaurant operators’ perspective.

To draw in and please more locavores, restaurant management can use buzzwords like “safe food,” “fresh food” and “environmental labels.” They should also provide their consumers with the backstory of menu items, including where food comes from, how it’s made and how it gets transported.

This study tests an adapted model built on TPB and advocates for sustainable production and consumption in line with the United Nations 2030 Agenda for Sustainable Development Goals.

This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques.

This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data.

The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation.

This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences.

This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services.

This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

This paper aims to validates a framework using the Uses and Gratifications Theory (UGT) to study the effect of values, i.e. Functional Value (FV), Social Value (SV), Emotional Value (EV) and Monetary Value (MV), on the Patronage Intention (PI) of Social Network Users (SNU’s) with mediating role of Perceived Usefulness (PU).

A survey method was used to collect responses from 302 SNUs, and the variance-based structural equation method was used to understand the relationships among the constructs.

The results found a significant positive effect of FV and EV on Perceived Usefulness (PU) and MV and PU on Patronage intention (PI) of SNUs. Further, PU partially mediated the relationship of EV with PI.

This study used the UGT to understand the effect of values on the PI of SNUs. This research study contributes to the existing social networks/social media literature.

The surge of artificial intelligence (AI) applications and subsequent adoption by consumers and marketers has ignited substantial research exploring the benefits and opportunities of AI. Despite this, little attention has been given to its unintended negative consequences. In this paper, the authors examine both the practitioner and academic sides of ethical AI. In doing so, the authors conduct an extensive review of the AI literature to identify potential issues pertaining to three areas: individual consumers, societal and legal. The authors identify gaps and offer questions to drive future research.

The authors review recent academic literature on AI in marketing journals, and top ethical principles from three top technology developers (Google, IBM and Meta) in conjunction with media reports of negative AI incents. They also identify gaps and opportunities for future research based on this review.

The bibliographic review reveals a small number of academic papers in marketing that focus on ethical considerations for AI adoption. The authors highlight concerns for academic researchers, marketing practitioners and AI developers across three main areas and highlight important issues relating to interactive marketing.

This paper highlights the under-researched negative outcomes of AI adoption. Through an extensive literature review, coupled with current responsible AI principles adopted by major technology companies, this research provides a framework for examining the dark side of AI.