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This conceptual paper aims to explore the possibility of human beings reaching a virtual form of immortality.

The paper is an investigation of the path from an early example of human knowledge to the birth of artificial intelligence (AI) and robots. A critical analysis of different point of views, from philosophers to scientists, is presented.

From ancient rock art paintings to the moon landing, human knowledge has made a huge progress to the point of creating robots resembling human features. While these humanoid robots can successfully undertake risky tasks, they also generate ethical issues for the society they interact with.

The paper is conceptual, and it does attempt to provide one theory by which human beings can achieve the dream of immortality. It is part of a work in progress on the use of AI and the issues related to the creation/use of humanoid robots in society.

This paper provides an overview of some of the key issues and themes impacting our modern society. Its originality resides in the linking of human knowledge to collective knowledge and then of collective mind to the hyper-collective mind. The idea of humans reaching immortality is burdened by the imperative need to define ethical guidelines for the field of AI and its uses.

While service failures and recoveries (SFR) constitute a well-explored research domain, such negative consumption experiences have been understudied in the luxury context. The current study undertakes a systematic review to capture current knowledge and stimulate research in this vital domain.

This study adopts a systematic literature review methodology and employs the Theory-Context-Characteristics-Methods (TCCM) framework.

Guiding theories, industry and national contexts, relevant constructs and their relationships, and research methods employed in studying SFR in luxury consumption are identified and synthesized.

A comparative analysis of the luxury SFR with broader extant knowledge is offered. Further, hospitality is revealed as the dominant context, meriting its emphasis.

The formalisation – switch from the informal to the formal sector – of micro, small and medium enterprises (MSMEs) has serious ramifications on the Egyptian economy. This study investigates the effect of the factors perceived by Egyptian informal entrepreneurs to encourage/deter formalisation on those entrepreneurs' intentions of formalising their MSMEs. Social media (SM) usage is a novel factor whose impact on the intention of formalisation is also examined.

The conceptual framework of the theory of planned behaviour (TPB) is used, and a logistic regression model is utilised. Relevant data were collected from self-assessment questionnaires of a sample of Egyptian informal female and young male entrepreneurs, who constitute the majority of informal entrepreneurs in Egypt.

Results reveal that for female entrepreneurs, only the support of the government and other institutions positively affects their intention of formalisation, whilst direct costs and lack of family support affect their intention negatively. For young male entrepreneurs, the number of employees and prospects of contract enforcement positively affect their intention of formalisation, whilst being involved in a trading activity affects it negatively. For both groups, higher levels of education and SM usage adversely affect their intention of formalisation. These varying results have a crucial policy implication: the one-size-fits-all public policies intended to stimulate formalisation might not work, and thus, more tailored policies are required.

Worldwide, research on the impact of SM on the formalisation of MSMEs is scant, if existent. In Egypt, research on MSMEs is limited, those focusing on the impact of SM on Egyptian MSMEs are even scarcer and those targeting SM's effect on their formalisation are absent.

This study aims to explore the role of digital technologies in tourism entrepreneurship. In particular, the main objective of this research is to examine the relationships among proactiveness, innovativeness, digitalization, and firm performance and growth in the hotel industry.

The data for this investigation were collected from 110 one- or two-star hotels that were operating in Poland during the time of this research. This study employs PLS-SEM to analyze the relationships among the examined variables.

The results show that digitalization has a significantly positive impact on a hotel’s performance. Moreover, digitalization mediates the impact of entrepreneurial behaviors on performance. In particular, digitization is a full mediator for the impact of proactiveness on firm growth and innovation on market performance. Additionally, there is a partial complementary mediation effect of digitalization in the case of impact of innovativeness on firm growth; digitization is not a mediator for the impact of proactiveness on firm growth.

Previous studies have not captured the relationships among entrepreneurship, digitalization, and performance; this study helps to fill the gap and examine these associations in the hospitality industry. The outcome of this study provides valuable insights for hoteliers for understanding the role (and importance) of digitalization in the context of proactiveness and innovativeness.

The nature and amount of data that public organizations have to monitor to counteract corruption lead to a phenomenon called “KPI overload”, consisting of the business analyst feeling overwhelmed by the amount of information and resulting in the absence of appropriate control. The purpose of this study is to develop a solution based on Artificial Intelligence technology to avoid data overloading and, at the same time, under-controlling in business process monitoring.

The authors adopted a design science research approach. The authors started by observing a specific problem in a real context (a healthcare organization); then conceptualized, designed and implemented a solution to the problem with the goal to develop knowledge that can be used to design solutions for similar problems. The proposed solution for business process monitoring integrates databases and self-service business intelligence for outlier detection and artificial intelligence for classification analysis.

The authors found the solution powerful to solve problems related to KPI overload in process monitoring. In the specific case study, the authors found that the combination of Business Intelligence and Artificial Intelligence can provide a significant contribution to the detection of fraud, corruption and/or policy misalignment in public organizations.

The authors provide a big-data-based solution to the problem of data overload in business process monitoring that does not sacrifice any monitored Key Performance Indicators and that also reduces the workload of the business analyst. The authors also developed and implemented this automated solution in a context where data sensitivity and privacy are critical issues.