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Smart scenarios related to industries or cities, characterized by intensive technology transfer and use of innovative and disruptive technologies, have been in the spotlight either on academic or organizational discussions, especially those with a technocentric focus. Among these technologies, artificial intelligence (AI) emerges as the most challenging one due to its complexity. Therefore, this chapter aims to address AI, in particular the future of the labor market, exploring the challenges regarding the skills required in the context of AI technology, addressing its uses, challenges, and benefits. In order to achieve this goal, a systematic review was conducted on the extant literature using the methodology Methodi Ordinatio. The results show that the current literature is gradually changing from a more critical and negative view of AI to a more optimistic one, with more positive approaches and expectations regarding its benefits. As practical implications, the findings can be used as a guide for governments to develop strategies aiming to deal with upcoming challenges, especially regarding future jobs and employability.

This viewpoint is a response to Yeoman's (2022) editorial on Sunderland AFC and the future of tourism. This viewpoint aims to outline the lessons one can learn from Star Wars about the future of tourism.

The paper reviews the live-action movies and series of the Star Wars franchise.

The paper derives specific conclusions in the following directions: the future technology in travel, tourism and hospitality; the tourists' motivation and behaviour; the management of travel, tourism and hospitality companies; destination management; economy and society and lessons from the franchise.

This is one of the first papers to elaborate on the lessons one can learn about the future of tourism from the Star Wars live-action movies and series.

This paper aims to challenge the fashion of ubiquitous artificial intelligence (AI) and the effects which it will have upon society. In doing so it argues that the effects of AI will be minimal but important.

This argument is based upon the Socratic method and explores the Utilitarian background in which AI is based while drawing upon classical literature and other examples to illustrate the argument.

The findings are encompassed in the argument and show that we need to be more open and careful when considering AI and its effects. We also need to be more realistic when considering potential benefits.

This argument has significant implications for the adoption of AI.

The social implications are equally profound and will impact upon our application of AI solutions to current problems and upon humanity more generally.

This is the first paper which relates AI to human successes.

The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

This paper aims to explore the past and future impacts of automation on family businesses, with a focus on the opportunities for human capital empowerment.

This paper draws upon a contemporary literature search to examine a range of scholarly and practitioner perspectives of the challenges and benefits of automation, exploring the evolvement towards hyperautomation and the empowerment of human capital in family businesses.

Automation, transforming to hyperautomation, general purpose artificial intelligence (AI) and beyond has the possibility of radically improving productivity. Fear of job obsolescence has been present since the birth of modern automation, and whilst some jobs are at risk of redundancy, a net gain towards higher-skilled labour is already evident. Family business leaders must be prepared to react appropriately to the accelerating war for talent by implementing a strategy for human capital empowerment.

This unique paper synthesises developments in automation and proposes a future perspective centred upon the empowerment of human capital in family businesses.

Artificial intelligence (AI) has been widely used as a financial technology (fintech) in the mobile banking (M-banking) domain. However, in the literature, how AI affects users' perceptions of social support and the users' satisfaction and continuance intention (CI) remains unknown. To fill this gap, the two core characteristics of AI, perceived intelligence (PI) and perceived anthropomorphism (PA), are combined with social support theory (SST) (including informational support (IS) and emotional support (ES)) to develop a research model to investigate how PI and PA affect IS and ES, which in turn affect users’ M-banking satisfaction and CI.

This study adopted a random probability sampling method to collect a total of 360 valid responses to verify the proposed model. Partial least squares (PLS) was employed for data analysis.

The results showed that PI and PA both have a significant positive impact on consumers' perception of social support (IS and ES). IS was a direct driver of satisfaction and CI. Surprisingly, although ES was positively associated with satisfaction, the study found that higher levels of ES will decrease CI. This study exposed how AI affects consumers’ satisfaction and CI through SST, and the role of AI in M-banking applications has been further confirmed.

This study expanded the SST to creatively integrate with AI features to reveal the impact of PI and PA on IS and ES, which in turn influence users' M-banking usage.

This paper aims to examine the opportunities and challenges of using ChatGPT in higher education. Furthermore, it is also discuss the potential risks and plunders of these tools.

The paper discuss the use of artificial intelligence (AI) in academia and explores the opportunities and challenges of using ChatGPT in higher education. It also highlights the difficulties of detecting and preventing academic dishonesty and suggests strategies that universities can adopt to ensure ethical and useful use of these tools.

The paper concludes that while the use of AI tools, ChatGPT in higher education presents both opportunities and challenges. The universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools. This paper further suggests that universities should develop policies and procedures, provide training and support, to detect and prevent cheating intentions.

The paper provides insights into the opportunities and challenges of using ChatGPT in higher education, as well as strategies for addressing concerns related to academic dishonesty. The paper further adds importance to the discussion on the ethical and responsible use of AI tools in higher education.

Many decision rules are rational but opaque, and many others are irrational but transparent. This paper aims to propose a theoretical framework to operationalize opacity in decision-making – the degree to which a decision rule is intelligible to the decision maker.

The authors operationalize opacity and discuss the implication of opaque decision-making in organizational settings through a typology, where decision rules can be rational or irrational and opaque or transparent.

The authors show that opacity is asymmetric as different organizational actors possess different degrees of knowledge about how the decision rules work. Organizational actors often opacify the decision rules to increase their power (based on asymmetric knowledge). Opacity also presents a significant impact on organizational accountability, as transparent organizations are more reputable.

This contribution represents the first theoretical and methodological articulation of opacity in decision-making, within a bounded and ecological rationality framework; it also sheds new light on the role of cognitive biases in organizational settings.