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In an era of polycrisis, we argue that responsible leaders need to unlearn common thinking patterns imprinted by old (management) paradigms in order to find new solutions to the grand challenges of our time. To be able to overcome the “crisis of the imagination” and spur narratives about more sustainable futures, leaders need to update and restructure their skill sets and invest in developing anticipatory and futures (thinking) skills, as well as futures literacy as a competence. To achieve this on the student level, we also need to rethink business and management education at the university level by challenging the ways we teach, i.e., teaching pedagogics, as well as the content and story we want to tell about the future of management. Thus, with this chapter, we aim to rethink pedagogical methods and tools by introducing educators to potential pathways for equipping students with adequate skills to be able to “use-the-future”. As the process of unlearning is difficult, we argue that we need to venture out of the business discipline and push the barriers of the business and management curriculum so as to be able to further unleash creativity and imagination. To achieve this aim, we propose the integration of methods and approaches from art-related disciplines, such as theater, visual arts, or design, into the business curriculum.

The purpose of this study is to provide an overview of artificial intelligence (AI) in the talent management sphere. The study seeks to contribute to the body of knowledge with respect to human resource management and AI by conducting a literature review on the integration of AI in talent management, synthesising existing approaches and frameworks, as well as emphasising potential benefits.

The study adopts desk research, computational literature review (CLR) and uses topic modelling [with bidirectional encoder representations from transformers (BERTopic)] to throw light on the diffusion of AI in talent management.

The study’s main finding is that the area of AI in talent management is on the verge of gradual development and is in tandem with the growth of AI. We deduced that there is a link between talent management practices (planning, recruitment, compensation and rewards, performance management, employee empowerment, employee engagement and organisational culture) and AI. Though there are some known fears with regards to using the innovation, the benefits outweigh the demerits.

The current study has some limitations. The scope and size of the sample are the primary limitations of this study. No form of qualitative analytics was used in this study; as a result, the information obtained was limited. The study provides a snapshot of AI in talent management and contributes to the lack of literature in the joint fields. Also, the study provides practitioners and experts an overview of where to target investments and resources if need be.

The originality of this study comes from the combination of CLR methods and the use topic modelling with BERTopic which has not been used by previous reviews. In addition, the salient machine learning algorithms are identified in the study, which other studies have not identified.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

The purpose of this paper is to investigate the role of Customer Participation (CP) in the effectiveness of New Service Development (NSD) by examining the moderating roles of Customer Empowerment (CE) and Customer Satisfaction (CS). The research reduces the risk of failure of the NSD process and/or improves the NSD processes used by companies through the consideration of the results in the practical dimension.

This study investigates the effects of CP at different stages of NSD using a quantitative approach. Data were collected through an online survey questionnaire. Smart PLS was used to analyse the data collected from 509 newsreaders and users of the news agency’s application.

The model confirmed that CE has an impact on the effectiveness of NSD in the idea generation and commercialization stages, but not in the development stage. Empowerment and customer satisfaction did not influence the three stages of NSD indirectly but directly. The results show that CP, CS and CE do not always have a direct or indirect effect on the development of new services. Therefore, in order to design new service development projects, media news companies need to determine the level of user cooperation.

The lack of objective data, especially on company performance, forces researchers to use questionnaires to analyse NSD effectiveness. Another limitation is that newspaper users answered the questionnaires, which creates “common method variance.”

Researchers on NSD effectiveness must use questionnaires due to a lack of objective data, especially on company performance. Another limitation is “common method variance” from newspaper users answering questionnaires.

This paper is a response to a perceived need for an examination of how new service development can be successful and effective.

This study aims to investigate the impact of service quality (SQ), perceived value (PV) and consumer satisfaction on Thai street food, with customer satisfaction (CS) as a mediator for customer loyalty and repurchase intention (RI). It also explores how consumer trust (CT) in Thai street food safety moderates these relationships.

Structural equation modelling (SEM) was utilised to analyse the complex interrelationships between various constructs. Multi-group analyses were conducted to investigate the moderating effects of CT on the structural model, considering two distinct groups based on trust levels: low and high.

The findings revealed that SQ and PV significantly influenced CS and behavioural intention, while the perceived quality of Thai street food had no significant impact on post-COVID-19 consumer satisfaction. The study highlighted the critical role of CT in moderating the relationships between SQ, PV and CS, with distinct effects observed in groups with varying trust levels.

The research emphasises the importance of enhancing SQ and delivering value to customers in the context of Thai street food, which can contribute to increased CS, RI and positive word-of-mouth. Furthermore, the study underscores the critical role of building CT in fostering enduring customer relationships and promoting consumer satisfaction and loyalty.

This research offers valuable insights into consumer behaviour and decision-making processes, particularly within the realm of Thai street food. It underscores the significance of understanding and nurturing CT, especially in the post-COVID-19 landscape, emphasising the need for effective business strategies and consumer engagement.