Abstract Artificial intelligence (AI) is at the forefront of a revolution in business and society. AI affords companies a host of ways to better understand, predict, and engage customers. Within marketing, AI’s adoption is increasing year-on-year and in varied contexts, from providing service assistance during customer interactions to assisting in the identification of optimal promotions. But just as questions about AI remain with regard to job automation, ethics, and corporate responsibility, the marketing domain faces its own concerns about AI. With this article, we seek to consolidate the growing body of knowledge about AI in marketing. We explain how AI can enhance the marketing function across nine stages of the marketing planning process. We also provide examples of current applications of AI in marketing.
Artificial intelligence (AI) is (re)shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications (will) provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being.
The chapters in this book explore the ethical dynamics between leaders and followers in business and in society as a whole. They argue that power and authority in today's world stem not from position or coercion, but from trust, commitment, and values shared with those who are led. The authors raise important questions such as: How do people give and get trust? What moral hazards are inherent in transformational and charismatic leader/follower relationships? What roles do deception and self-deception play in giving and receiving power? The reader will gain a better understanding of the complex moral interaction of leaders and followers and why healthy moral relationships between leaders and followers are central to effective leadership. Practitioners, academics, and students will find this passionate collection invaluable in understanding the exciting and often controversial field of leadership and ethics.
As artificial intelligence (AI) becomes integral to organizational transformation, ethical adoption has emerged as a strategic concern. This paper reviews ethical theories, governance models, and implementation strategies that enable responsible AI integration in business contexts. It explores how ethical theories such as utilitarianism, deontology, and virtue ethics inform practical models for AI deployment. Furthermore, the paper investigates governance structures and stakeholder roles in shaping accountability and transparency, and examines frameworks that guide strategic risk assessment and decision-making. Emphasizing real-world applicability, the study offers an integrated approach that aligns ethics with performance outcomes, contributing to organizational success. This synthesis aims to support firms in embedding responsible AI principles into innovation strategies that balance compliance, trust, and value creation.
Aadarsh Padiyath, Casey Fiesler, Mark Guzdial
et al.
Computing ethics education aims to develop students' critical reflection and agency. We need validated ways to measure whether our efforts succeed. Through two survey administrations (N=474, N=464) with computing students and professionals, we provide evidence for the validity of the Critical Reflection and Agency in Computing Index. Our psychometric analyses demonstrate distinct dimensions of ethical development and show strong reliability and construct validity. Participants who completed computing ethics courses showed higher scores in some dimensions of ethical reflection and agency, but they also exhibited stronger techno-solutionist beliefs, highlighting a challenge in current pedagogy. This validated instrument enables systematic measurement of how computing students develop critical consciousness, allowing educators to better understand how to prepare computing professionals to tackle ethical challenges in their work.
In large-scale software development, understanding the functionality and intent behind complex codebases is critical for effective development and maintenance. While code summarization has been widely studied, existing methods primarily focus on smaller code units, such as functions, and struggle with larger code artifacts like files and packages. Additionally, current summarization models tend to emphasize low-level implementation details, often overlooking the domain and business context that are crucial for real-world applications. This paper proposes a two-step hierarchical approach for repository-level code summarization, tailored to business applications. First, smaller code units such as functions and variables are identified using syntax analysis and summarized with local LLMs. These summaries are then aggregated to generate higher-level file and package summaries. To ensure the summaries are grounded in business context, we design custom prompts that capture the intended purpose of code artifacts based on the domain and problem context of the business application. We evaluate our approach on a business support system (BSS) for the telecommunications domain, showing that syntax analysis-based hierarchical summarization improves coverage, while business-context grounding enhances the relevance of the generated summaries.
Business Process Model and Notation (BPMN) is a widely used standard for modelling business processes. While automated planning has been proposed as a method for simulating and reasoning about BPMN workflows, most implementations remain incomplete or limited in scope. This project builds upon prior theoretical work to develop a functional pipeline that translates BPMN 2.0 diagrams into PDDL representations suitable for planning. The system supports core BPMN constructs, including tasks, events, sequence flows, and gateways, with initial support for parallel and inclusive gateway behaviour. Using a non-deterministic planner, we demonstrate how to generate and evaluate valid execution traces. Our implementation aims to bridge the gap between theory and practical tooling, providing a foundation for further exploration of translating business processes into well-defined plans.
The increasing integration of artificial intelligence (AI) into medical diagnostics necessitates a critical examination of its ethical and practical implications. While the prioritization of diagnostic accuracy, as advocated by Sabuncu et al. (2025), is essential, this approach risks oversimplifying complex socio-ethical issues, including fairness, privacy, and intersectionality. This rebuttal emphasizes the dangers of reducing multifaceted health disparities to quantifiable metrics and advocates for a more transdisciplinary approach. By incorporating insights from social sciences, ethics, and public health, AI systems can address the compounded effects of intersecting identities and safeguard sensitive data. Additionally, explainability and interpretability must be central to AI design, fostering trust and accountability. This paper calls for a framework that balances accuracy with fairness, privacy, and inclusivity to ensure AI-driven diagnostics serve diverse populations equitably and ethically.
Alejandro Valencia-Arias, Lucía Palacios-Moya, Wilmer Londoño-Celis
et al.
Interest in sustainable entrepreneurship has grown in both academic and business circles, with the aim of promoting the creation of environmentally and socially responsible enterprises. However, achieving true sustainability in entrepreneurship is fraught with complex challenges and dilemmas. The aim of this study is to examine research trends. The PRISMA-2020 methodology was used to analyse publications in the Scopus and Web of Science databases. The analysis included the examination of publications by year, main references, thematic evolution, keyword co-occurrence network, emerging and growing words. The results showed a remarkable growth of scientific literature in the years 2022 and 2023. The main research references include Wagner M. as well as journals such as Sustainability, and the influence of the United States, Pakistan, and Germany on scientific production. The thematic evolution showed a shift towards themes such as university support, sustainability, and environmental values. The main thematic clusters were characterised by the high conceptual affinity between terms such as Entrepreneurial Intention and Entrepreneurship. Emerging terms such as Circular Economy and Subjective Norms indicate a growing interest in specific aspects of sustainability. The text provides a strong basis for future research and the development of research agendas to address the identified gaps.
The study aims to determine the impact of off-balance sheet items on business leadership, focusing on the case of technical efficiency in 12 private banks operating in Algeria between 2011 and 2020. Technical efficiency (the dependent variable) was measured using the Data Envelopment Analysis (DEA) method by applying the variable return to scale model with input orientation (BCC-I) based on deposits and general exploitation expenditures as inputs and loans and net profit as outputs. As for the Off-Balance Sheet Items (the independent variable), they were expressed by the ratio of the total off-balance sheet financing to total assets, with the help of a set of control variables that reflect the bank's performance level. To measure the impact, panel data models were used. The study concluded that the business leadership in the private banks under investigation does not optimize their resources and that the off-balance sheet items significantly negatively impact these banks’ technical efficiency. This is attributed to the unregulated expansion of activities and operations related to off-balance sheet items by the business leadership in some banks, which has had negative effects on performance due to high costs.