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The management of consumer privacy has become a critical concern for organizations in the age of artificial intelligence–powered marketing. The impact of data on the market environment has brought both benefits and challenges, with marketers gaining valuable insights but also raising privacy concerns. As artificial intelligence–powered marketing advances, consumer vulnerability increases due to the sensitivity of collected data. This vulnerability leads some consumers to resort to falsifying information, posing a significant threat to the digital economy. Privacy empowerment and customer control play a vital role in addressing these challenges. This chapter explores the influencing factors and ethical considerations surrounding data falsification. It also discusses strategies to mitigate perceived vulnerability through privacy controls and explores the consequences of data breaches and customer vulnerability. The chapter further emphasizes the need for organizations to balance benefits, risks, and customer trust while harnessing the value of customer data. An ethical framework for data privacy marketing audits is proposed to help organizations assess their data practices responsibly and competitively. By integrating personal data protection strategies within an ethical framework, organizations can protect consumer privacy, enhance customer trust, and maintain their competitive edge in the market.

In the mid-2000s, the operator of New York City’s mass transit network committed more than a half-billion dollars to military contractor Lockheed Martin for a security technology capable, in part, of inferring threats based on analysis of data streams, of developing response strategies, and taking automated action toward alerts and calamities in light of evolving circumstances. The project was a failure. This chapter explores the conceptualization and development of this technology – rooted in cybernetics – and compares its conceptual underpinnings with some situated problems of awareness, communication, coordination, and action in emergencies as they unfold in one of the busiest transport systems in the world, the New York subway. The author shows how the technology, with all the theatrical trappings of a “legitimate” security solution, was apparently conceived without a grounded understanding of actual use-cases, and the degree to which the complex interactions which give rise to subway emergency can be anticipated in – and therefore managed through – a technological system. As a case-study, the chapter illustrates the pitfalls of deploying technology against problems which are not well-defined in the first place, to the neglect of investments against much more fundamental problems – such as inadequate communication systems, and unstable relationships with emergency response agencies – which might offer guaranteed benefits, and indeed lay a firm groundwork for future deployment of more ambitious technology.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

This chapter on anti-racism struggles applies an anti-racist activist framing, both critically examining and recognising the milestones achieved through centuries of pro-justice and anti-racism struggles. It delves into the arduous journey that the global fight for racial equity has undergone and highlights the significant progress as well as setbacks experienced during this lengthy struggle. The earliest history of the fight against racial oppression and domination goes back to anti-slavery and anti-colonial movements. Scholars have analysed the emergence, development and state of global anti-racism struggles in a variety of ways. I approach this subject from a sociological perspective, highlighting the role of social structures, groups and institutions that have contributed to shaping the outcomes of anti-racist initiatives. While recognising the role of individuals and leading political activists, this chapter emphasises anti-racism as a collective social justice struggle. To do this, I explore various local and global anti-racism endeavours and examine how they may influence discussions on race, racism and racial equity and their evolving trajectories across different societies.

Artificial intelligence (AI) is revolutionizing businesses and daily life, with AI-powered technologies like personal assistants and medical diagnostic systems transforming how we interact and make decisions. However, the ethical implications of these technologies cannot be ignored. AI systems can produce biased results and decisions if not designed to be fair and unbiased. Corporate digital responsibility (CDR) provides a valuable framework for addressing these ethical dilemmas. Service organizations need to navigate CDR issues across the data and technology life-cycle stages (e.g., their creation, operation, refinement, and retention) and across its digital service ecosystem (including its external business partners). Despite the risks associated with poor CDR practices, companies may adopt them to benefit from data monetization, enhanced customer experience, and productivity improvement. To mitigate these risks and build a strong CDR culture, organizations need to establish ethical norms, prioritize customer privacy, and ensure equitable power dynamics with business partners. The emergence of generative AI poses enhanced CDR challenges, such as AI complexity, monitoring, accountability, and workforce changes. Going forward, CDR is a crucial framework for firms to address the needs of their multiple stakeholders and to ensure sustainable business practices in the increasingly digital service world.

While most West European nations were formed around pre-existing entities that could be called “countries” before the modern age, this was not the case in the Middle East. Some entities, like Egypt, did have a clear political and cultural identity before colonialism, others, like Algeria, did not. This chapter discusses the four states of the Maghreb: Morocco, Algeria, Tunisia and Libya, through the perspective of “country creation” going into and coming out of colonial rule. We can see here two “models” of fairly similar types of historical development, one showing a gradual process through a protectorate period to relatively stable modern nations, another through violent conquest and direct colonization ending in violent liberation and military and wealthy but fragile states. The article asks whether these models for the history of country creation and the presence or absence of pre-colonial identities can help explain the modern history and nature of these states in the Arab Spring and the years thereafter. Then, a more tentative attempt is made to apply these models to two countries of the Arab east, Syria and Iraq. While local variations ensure that no model can be transferred directly, it can show the importance of studying the historical factors that go into the transition from geographical region to a country with people that can form the basis of a nation.

This chapter investigates whether, and if so, how particular firms in a transition economy are involved in bribery. Built on pressure theories, we explain how the direct effects of firm characteristics and contextual characteristics determine firm bribery behavior. Entrepreneurs make choices based on perceptions of a specific pressure due to organizational characteristics (internal pressures) or due to context (external pressures). The relationship between firm characteristics, context, and bribery was estimated using unique data from a survey of 606 Vietnamese entrepreneurs. We controlled for various entrepreneurial, organizational, and industrial characteristics. The exploratory findings support firm attributes hypotheses, which is a negative relationship between firm size and bribery and a nonmonotonic U-shaped relationship between firm age and bribery. Besides, the effects of context on bribery are also found. Specifically, the result supports a positive relationship between competition and bribery and a negative relationship between the quality of the government and bribery.

In Morocco, as in many developing countries, environmental responsibility is not well integrated into corporate management at the operational, tactical, and strategic levels. While the management literature offers a rich body of knowledge on Corporate Social Responsibility (CSR) strategies and practices, less attention has been paid to exploring the complexity of environmental responsibility through the lens of corporate culture. This research aims to address this gap by examining the influence of cultural factors on the deployment of environmental responsibility using Johnson's (2000) model of corporate culture. This model identifies seven components of corporate culture: stories or myths, symbols, power structures, organizational structures, control systems, rituals and routines, and paradigms. Through a Moroccan industrial group case study, this chapter presents the successful deployment of environmental responsibility and describes how managing cultural factors facilitated this transition. This chapter also identifies the unique aspects of the group's culture that allowed redesigning the company's management systems. These insights offer valuable implications for managers and policymakers seeking to improve the environmental performance of large enterprises in developing countries.

Racial stigma and racial criminalization have been centralizing pillars of the construction of Blackness in the United States. Taking such systemic injustice and racism as a given, then question then becomes how these macro-level arrangements are reflected in micro-level processes. This work uses radical interactionism and stigma theory to explore the potential implications for racialized identity construction and the development of “criminalized subjectivity” among Black undergraduate students at a predominately white university in the Midwest. I use semistructured interviews to explore the implications of racial stigma and criminalization on micro-level identity construction and how understandings of these issues can change across space and over the course of one's life. Findings demonstrate that Black university students are keenly aware of this particular stigma and its consequences in increasingly complex ways from the time they are school-aged children. They were aware of this stigma as a social fact but did not internalize it as a true reflection of themselves; said internalization was thwarted through strong self-concept and racial socialization. This increasingly complex awareness is also informed by an intersectional lens for some interviewees. I argue not only that the concept of stigma must be explicitly placed within these larger systems but also that understanding and identity-building are both rooted in ever-evolving processes of interaction and meaning-making. This research contributes to scholarship that applies a critical lens to Goffmanian stigma rooted in Black sociology and criminology and from the perspectives of the stigmatized themselves.