While the technical application domain seems to be to most established field for AI applications, the field is at the very beginning to identify and implement responsible and fair AI applications. Technical, non-user facing services indirectly model user behavior as a consequence of which unexpected issues of privacy, fairness and lack of autonomy may emerge. There is a need for design methods that take the potential impact of AI systems into account.
Although governments are investing heavily in big data analytics, reports show mixed results in terms of performance. Whilst big data analytics capability provided a valuable lens in business and seems useful for the public sector, there is little knowledge of its relationship with governmental performance. This study aims to explain how big data analytics capability led to governmental performance. Using a survey research methodology, an integrated conceptual model is proposed highlighting a comprehensive set of big data analytics resources influencing governmental performance. The conceptual model was developed based on prior literature. Using a PLS-SEM approach, the results strongly support the posited hypotheses. Big data analytics capability has a strong impact on governmental efficiency, effectiveness, and fairness. The findings of this paper confirmed the imperative role of big data analytics capability in governmental performance in the public sector, which earlier studies found in the private sector. This study also validated measures of governmental performance.
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People with disabilities (PWDs) face discrimination in the hospitality workplace. The aim of this paper is therefore to frame issues surrounding the employment of PWDs in the hospitality industry in normative ethical terms. To achieve this aim, we conducted twenty-eight semi-structured interviews with owners/managers of hospitality businesses and other relevant stakeholders. Drawing on the ethics of justice and ethics of care, our study found that when organisations demonstrated to their employees and other stakeholders the fairness in the procedures taken to implement PWD inclusion actions, the inclusion actions were significantly supported by coworkers, and the organisations were able to achieve distributive justice and care for PWDs. This study, thus, demonstrated that organisational members were willing to take part in caring actions for employees with disabilities (EWDs) not only when they perceived that inclusion actions for EWDs were procedurally fair, but also when they perceived that the PWDs deserved distributive justice outcomes.
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