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This paper explores organization-level racialized work strategies for maintaining racialized organizations (Ray, 2019). It focuses on intentional actions to maintain dominant racial norms, demonstrating how work strategies are informed by dominant racial structures that maintain racial inequities.

We compiled a chronological case study (Yin, 2012) based on 168 news media articles and various organizational documents to examine responses to athlete protests at the University of Texas at Austin following the death of George Floyd. Gioia et al.’s (2013) method uncovered how dominant racial norms inform organizational behaviors.

The paper challenges institutional theory neutrality and identifies several racialized work strategies that organizations employ to maintain racialized norms and practices. The findings provide a framework for organizations to interrogate their strategies and their role in reproducing dominant racial norms and inequities.

In 2020, the Black Lives Matter (BLM) movement was reinvigorated within sporting and corporate domains. However, many organizations engaged in performativity, sparking criticism about meaningful change in organizational contexts. Our case study examines how one organization responded to athlete activists’ BLM-fueled demands, revealing specific racialized work strategies that maintain structures of racism. As organizations worldwide disrupt and discuss oppressive structures such as racism, we demonstrate how organizational leadership, while aware of policies and practices of racism, may choose not to act and actively maintain such structures.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

There is evidence that quality improvement projects developed with the participation of patients and family members are more likely to result in a sustainable change. To identify the intervening factors is an important step in promoting and supporting patient and family members’ engagement.

A survey was carried out with 90 hospitals. A total of 35 intervening factors were evaluated by the healthcare professionals from the quality area using a Likert scale. Factor analysis was applied to identify the relationship among the factors and cluster analysis and the standardized scores for each new latent variable were obtained to observe the association between them and hospitals profile. Cluster analysis allowed to group the hospitals with similar responses and to analyze whether there was any association with the profile of the institutions.

A total of ten intervening factors are identified: two in the financial dimension, five in the structural and three in the personal and cultural. The standardized scores of latent variables suggest that the financial factors could be affected by the hospital capacity. The structural factors could be impacted by the accreditation status, location (region) and administrative control (ownership). And the personal and cultural factors could be by the location and dominant organizational culture. All of factors are influenced by the performed quality management activities. The cluster analysis allowed the identification of three groups in the financial dimension, and four in the other two dimensions. Except for the accreditation status in the personal and cultural dimension, no evidence of association between the groups and the variables raised to characterize the profile of the hospitals was found.

The study contributed to identify the relationship among the intervening factors turning possible to simplify and reduce them more comprehensively than those originally identified in the literature and at the same time maintaining the representativeness of the original variables.