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This study aims to analyze corporate mail and wire fraud penalties, using bounded rationality in decision-making and assessing internal and external influences on prosecutorial choices.

The study analyzed 467 cases from 1992 to 2019, using data from the Corporate Prosecution Registry of the University of Virginia School of Law and Duke University School of Law. It examined corporations facing mail and wire fraud charges and other fraud crimes. Multiple regression linked predictor variables to the dependent variable, total payment.

The study found that corporate penalties tend to be lower for financial institutions or corporations in countries with US free trade agreements. Conversely, penalties are higher when the company is a U.S. public company or filed in districts with more pending criminal cases.

This study’s originality lies in applying the bounded rationality model to assess corporate prosecutorial decisions, unveiling external factors’ influence on corporate penalties.

As internet dividends are gradually disappearing, loyalty programs have become the panacea for monetizing traffic, attracting new customers and retaining existing customers. Improving their effectiveness has thus become key to enterprises’ market competitiveness. However, member customers’ hedonic adaptation to this relationship strategy undermines its effectiveness. Based on the hedonic adaptation theory, this study aims to analyze the process of member customers' hedonic adaptation to preferential treatment in loyalty programs and explore the boundary conditions of alleviating this effect.

This study surveyed 271 member customers in China and tested the hypothesized relationships using structural equation modeling and multigroup analysis.

Preferential treatment suffers from hedonic adaptation to member customer engagement and customer gratitude, and customer tenure is a key condition for these effects. Customer gratitude is an intermediary mechanism that explains the hedonic adaptation effect of preferential treatment to member customers engagement. In addition, the structural characteristics of loyalty programs form the boundary condition that alleviates hedonic adaptation. The authors found that high-tier and -payment strategies are more likely to mitigate hedonic adaptation of preferential treatment to customer gratitude.

This study elucidates the factors that influence the effectiveness of preferential treatment and provides constructive insights into customer relationship management and for improving enterprise performance.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

This study employs the social ecology model to comprehensively explore the complex challenges young Black men face in South Africa and aims to highlight the importance of collaboration in addressing these multifaceted issues.

A multidisciplinary approach combines insights from sociology, education and the health literature with regard to government reports and academic data, and provides a holistic analysis of challenges faced by young Black men. Furthermore, it emphasises formal and informal learning, social and environmental influences and health disparities.

Young Black men in South Africa encounter complex challenges throughout their developmental journey, including limited family support, educational barriers, financial constraints, societal expectations and health disparities. Therefore, collaboration among stakeholders is essential for creating an equitable and inclusive environment that supports their development.

This research provides a comprehensive understanding of the challenges faced by young Black men in South Africa by emphasising the interconnectedness of informal education, economic empowerment and healthcare. Future research should focus on longitudinal studies, cultural influences and international comparisons, informing evidence-based interventions for a more equitable society.