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Raimondo C: Corporate Misconduct and
Ethics

Corporate Misconduct and Ethics

Case Studies: from Big Pharma to Michelin

Perspectives on Process Organization Studies

Process Studies in Extreme Contexts

Organizing on the Precipice

Moderne Managementansätze

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Dictatorship of Big Capital

Routledge Studies in Trust Research

Corporate Self-Financing and Market Trust examines whether and under what conditions internally generated financial resources strengthen investor trust in listed food and beverage companies. Combining corporate finance theory with comparative evidence from the United States, developed European markets, and emerging European markets, the book develops a trust-centered model of internal financing. It distinguishes internal financing capacity from self-financing and shows that retained earnings, operating cash flow, liquidity, leverage, governance, ESG disclosure, and capital allocation discipline do not influence market trust independently. Their effects depend on institutional context and the credibility with which financial decisions are communicated.Drawing on company-level data for 2019-2024, the book integrates financial ratio analysis, non-parametric tests, panel regressions, moderation analysis, structural equation modeling, and comparative case studies. It also introduces a multidimensional Investor Trust Proxy based on observable market measures. The book will be valuable to researchers and advanced students in corporate finance, accounting, agribusiness, and sustainability, as well as managers, investors, and policymakers seeking to understand how financing decisions become credible market signals.

A Comparative Study of Food and Beverage Companies in the U.S. and Europe

Corporate Self-Financing and Market Trust

Implement trusted AI systems that deliver measurable business value while managing risk, compliance and long-term performance. Decision-Quality AI by Eva-Marie Muller-Stuler is a practical guide for data, product and technology leaders responsible for turning AI ambition into real-world outcomes. Covering the complete AI lifecycle from strategy and team design to deployment and governance, it provides the frameworks and technical foundations needed to develop AI products that are effective, responsible and aligned with business goals. Designed for leaders implementing AI at scale, this book helps you move beyond experimentation and hype to build AI solutions that solve genuine business challenges while meeting regulatory and operational requirements. You will learn how to: - Define AI use cases that address real business needs - Build teams, processes and governance for AI delivery - Develop, test and deploy AI with confidence - Manage risk, compliance, security and transparency - Monitor performance throughout the AI lifecycle Decision-Quality AI combines responsible AI principles with the practical disciplines required for successful implementation. It explores areas such as MLOps, ModelOps, AIOps, DevSecOps and cybersecurity, giving you a complete framework for delivering AI that creates lasting impact. Whether you are launching your first AI initiative or scaling enterprise-wide adoption, this book provides the tools, processes, and leadership guidance you need to build trusted AI systems that deliver results. Themes include: AI development, AI governance, AI security, MLOps, ModelOps, risk management, DevSecOps, data architecture, AI strategy

Grasp how to deliver fully deployed, scalable, trusted and useful AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecycle of AI development.

From AI Ambition to Operational Success

Decision-Quality AI

Routledge Research in Media Law

This book considers whether news gatherers should be required to disclose the identity of anonymous sources used in their stories by courts or other bodies. The vast majority of media self-regulatory codes impose an obligation not to disclose the identity of such sources, but many legal systems have traditionally been reluctant to offer such a degree of protection to anonymous sources, or any at all. However, the latter part of the twentieth century and early twenty-first century has seen an explosion in the number of such 'source protection' laws, and much judicial and legislative activity to change existing laws.Drawing on media and communications theories the book identifies a number of different theoretical justifications for source protection laws and analyzes whether the application of existing laws are consistent with any of these theories. Using legal materials and codes from a wide variety of countries it considers whether there are any noticeable trends in how different countries address this issue. It explores the influence of the United States and the European Court of Human Rights' jurisprudence on the matter beyond their jurisdictions, and asks the question whether this is an area of law captured by 'globalisation,' or whether countries with different constitutional and media traditions have developed different approaches to 'source protection.'Finally having assess the arguments in support of source protection laws Damian Carney puts forward a model clause and model shield law for the protection of anonymous sources which is theoretically and practically robust.

This book considers whether news gatherers should be required to disclose the identity of anonymous sources used in their stories by courts or other bodies.

A Comparative, Theoretical and Critical Analysis

Journalists, Anonymous Sources and the Law

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI, and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact.Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments.You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behaviorFeaturing real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance.Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

This comprehensive textbook offers an up-to-date account of how organizations function in a rapidly changing world. Designed as a practical and accessible guide, it combines theoretical insights with real-world applications while presenting organizations as complex social systems shaped by people, culture, power and context.It introduces key questions such as:¿ What are organizations and why do they exist? ¿ How do they define goals and strategies? ¿ How are they structured and led? ¿ How do people, culture and identity shape organizational life? ¿ How do organizations interact with their environments?Chapters feature a range of thoughtfully designed learning tools, such as case studies, reflection boxes, in-depth features and paradox boxes that encourage students to explore tensions, dilemmas and competing perspectives in organizational life. Readers benefit from diverse examples drawn from global contexts and sustained attention to contemporary challenges such as digitalization, sustainability, legitimacy and organizational change.This textbook provides a strong foundation in organization theory and organizational behavior while developing the analytical and critical skills needed to understand and engage with contemporary organizations. Comprehensive online resources, including PowerPoint slides, flashcards and quizzes, are available at www.routledge.com/cw/skyttermoen.

Organizations in Context

Volume 27 explores critical intersections of professional responsibility, ethics, governance, and emerging technology issues in accounting and accounting education. Chapters focus on professional responsibility and financial mechanisms like stock option vesting and strike prices influence whistleblowing behavior and examine the role of corporate social responsibility and incentives in encouraging reporting ethical dilemmas. The impact of COVID-19 on corporate social disclosures and firm buybacks highlights evolving transparency and performance measures. Auditing practices are scrutinized through the lens of materiality and public interest, while academic dishonesty among business students is analyzed using ethical theory-based rationalizations. Emerging technologies are addressed by evaluating ChatGPT's ability to identify ethical issues compared to expert instructor materials and the collapse of QuadrigaCX underscores risks in cryptocurrency management and the importance of safeguarding digital assets. Research on Professional Responsibility and Ethics in Accounting is devoted to publishing high-quality research and cases that focus on the professional responsibilities of accountants and how they deal with the ethical issues they face.

Research on Professional Responsibility and Ethics in Accounting

Managing and Leading for Social Justice

Across clinics, classrooms, city halls, and financial systems, women continue doing the uncredited work of governing AI: deciding when systems can be trusted, paused, refused, and repaired. Governing the Default names this work as relational governance, demonstrating how leaders can turn critique of AI's extractive norms into operational practice. Bringing together industry and academic contributors, the volume reframes organizational care as governance designed into decision rights, feedback loops, oversight, and repair. Its copy-ready practices help leaders, educators, and policymakers replace opaque defaults with consent-first, benefit-sharing, repair-ready systems.

Governing the Default

Gender, Power, and Emerging Technology

A Genealogy of Business and Human Rights, 1974—2024

Capitalizing Human Rights

Corporate Misconduct and Ethics

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