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The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

The philosophical foundations determine how an academic discipline identifies, understands and analyzes phenomena. The choice of philosophical perspective is vital for both marketing and service research. This paper aims to propose a social and systemic perspective that addresses current challenges in service and marketing research by revisiting the philosophy of science debate.

The paper revisits the philosophy of science debate to address the implications of an emergent, complex and adaptive view of marketing and service research. It draws on critical realism by combining structuration and systemic perspectives.

A recursive perspective, drawing on structures and action, is suggested as it includes multiple actors’ intentions and captures underlying drivers of market exchange as a basis for developing marketing and service strategies in practice. This is aligned with other scholars arguing for a more systemic, adaptive and complex view of markets in light of emerging streams in academic marketing and service research, ranging from value cocreation, effectuation, emergence and open source to empirical phenomena such as digitalization, robotization and the growth of international networks.

The reciprocal dynamic between individuals and the overarching system provides a reflexivity approach intrinsic to the service ecosystem. This creates new avenues for research on marketing and service phenomena.

This paper discusses critics, conflicts and conceptualization in service research. It suggests a possible approach for service research and marketing scholars capable of responding to current complexities and turbulence in economic and societal contexts.

Digital transformation of organizations has major implications for required skills and competencies of the workforce, both as a prerequisite for implementation, and, as a consequence of the transformation. The purpose of this study is to analyze required skills and competencies for digital transformation using the context of robotic process automation (RPA) as an example.

This study is based on an explorative, thematic coding analysis of 119 job advertisements related to RPA. The data was collected from major online job platforms, qualitatively coded and subsequently analyzed quantitatively.

The research highlights the general importance of specific skills and competencies for digital transformation and shows a gap between available skills and required skills. Moreover, it is concluded that reskilling the existing workforce might be difficult. Many emerging positions can be found in the consulting sector, which raises questions about the permanent vs temporary nature of the requirements, as well as the difficulty of acquiring the required knowledge.

This paper contributes to knowledge by providing new empirical findings and a novel perspective to the ongoing discussion of digital skills, employment effects and reskilling demands of the existing workforce owing to recent technological developments and automation in the overall context of digital transformation.

The purpose of this paper used for catastrophe and pandemic preparedness was the craft of machine learning calculations. ML is the latest globe learning technique to assist in the identification and remediation of medical care catastrophes.

To the greatest extent possible, countries are terrified about debacles and pandemics, which, all in all, are exceptionally improbable occurrences. When health emergencies arise on the board, several issues arise for the medical team because of the lack of accurate information from numerous diverse sources, which is required to be available by suitable professionals.

Thus, the current investigation’s main objective is to demonstrate a structure that is dependent on the incorporation of recent advances, the Internet of Things and large information and which can settle this issue by using machine learning (ML) in all stages of catastrophe and providing accurate and compelling medical care.

The system upholds medical services characters by empowering information to be divided between them, enabling them to perform insightful estimations and enabling them to find significant, legitimate and precise patterns that are required for functional arrangement and better readiness in the event of crises. It is possible that the results of the system’s work may be used by the executives to assist chiefs in differentiating and forecasting the wellbeing repercussions of the fumbles.