Ritsumeikan Asia Pacific University

Este artículo analiza un importante número de referencias lingüísticas y geográficas encontradas en el tratado botánico ‘Umdat al-Ṭabīb fī-Ma‘rifat al-Nabāt, posiblemente escrito en la segunda mitad del siglo XI y cuya autoría ha sido atribuida a Abū al-Ḫayr. Se trata de una obra que, además de proporcionarnos una valiosa información de índole botánica, nos ofrece igualmente gran cantidad de datos sobre cómo era la vida y la sociedad andalusí en aquella época, así como la percepción que el autor de la obra tenía del mundo. La metodología que hemos seguido para la realización de este trabajo se ha basado en un análisis de carácter sociolingüístico y filológico de términos y expresiones que nos proporcionan información relacionada con las identidades y los territorios, y cuyo resultado apunta hacia la idea de la existencia de un cierto sentimiento comunitario y de pertenencia a un espacio geográfico en contraste con otros grupos lingüísticos, étnicos y religiosos existentes dentro y fuera de al-Andalus en el siglo XI. Este postulado nos parece de gran interés y relevancia para conocer mejor al autor de este tratado, la sociedad de aquel momento, y las características identitarias existentes en al menos una parte de la población.

The purpose of this study is to identify grey transaction behaviours that function as barriers to blockchain implementation in supply chain finance, explore which obstructions arise from these grey transaction behaviours and subsequently hinder blockchain implementation, and further measure the influence levels of the corresponding implementation barriers. The Delphi method and DANP are the main analysis methods used in this study. According to the analysis, three grey transaction behaviours that function as implementation barriers are identified, namely, kickbacks, internal and external accounting, and informal transaction relationships with banks. In addition, seven obstructions arise from these three barriers, and these obstructions can be adopted to explain why the three barriers hinder blockchain implementation. Finally, although internal and external accounting represents the main barrier, informal transaction relationships with banks may function as a critical underlying barrier that enhances the other two barriers. This study contributes in that it fills the gap of existing studies related to the intersection of supply chain finance and blockchain and provides a new perspective enabling practitioners to rethink how blockchain can be successfully implemented in the context of supply chain finance.

Purpose This study aims to investigate the driving factors that enhance the willingness to adopt Human–AI collaboration in green supply chains and examines the impact of psychological barriers on the transition from collaboration intentions to behavioral expectations. Design/methodology/approach A theoretical framework grounded in the Unified Theory of Acceptance and Use of Technology and the Uncanny Valley theory was empirically tested using survey data collected from Chinese manufacturing firms. A total of 467 valid responses were obtained across two independent samples collected at different time points. This dual-sample design captures perspectives from distinct groups and periods, providing broader insights into the proposed relationships. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to examine the theoretical framework. Findings The results show that performance expectancy, social influence and facilitating conditions significantly drive collaboration intentions, which, in turn, positively influence behavioral expectations. While emotion-driven digital trust conflicts showed no significant impact, societal fears remain a key barrier. Specifically, concerns over AI replacing human roles hinder the translation of intentions into behavioral expectations. Originality/value In addition to the identified driving factors, findings of this study emphasize the importance of addressing societal fears to ensure that Human–AI collaboration fosters a self-sustaining ecosystem, enabling continuous innovation in green knowledge generation and sustainable pollution control within green supply chains.

Purpose Along with the rapid development of the robotic technology, various service robots, such as service delivery robots, have been gradually applied in hospitality. Although previous studies have examined the advantages or future trends of service robots, the use of robotic technologies in different hotel departments or the effects of hotel robot adoption on the stay intention of consumers, limited studies investigated the emotional complexity, cognitive–analytical and emotional–social responses of service robots from the perspective of consumers, as well as their influences on consumers’ intention to stay at robot hotels. Hence, this study aims to examine emotional–cognitive–social responses of diverse service robots on consumers’ intention to stay at robot hotels. Design/methodology/approach This study adopted a mixed approach of qualitative (i.e. 18 in-depth interviews conducted with hotel technology managers) and quantitative (i.e. 449 questionnaire surveys collected among the young generation) research methods on the basis of the cognitive behavioral model. In the initial stage, descriptive statistics were presented. Thereafter, structural equation modeling was used for data analysis. Findings Findings indicated that compared with the ability in completing cognitive–analytical and emotional–social tasks, hotel service robots are more able to complete services that require high emotional complexity. Moreover, results illustrated that artificial intelligence (AI) robots significantly affect the intention of consumers to stay at robot hotels. Practical implications Hospitality practitioners can consider adopting AI robots (e.g. artificial intelligent robot for simple entertainment or communication) as their future strategic plans to enhance the intention of consumers to stay at robot hotels. Originality/value This study examined the extent to which hotel robots can overcome the shortage of robot service requiring high emotional complexity, evaluated the effectiveness of hotel robots in performing cognitive–analytical and emotional–social tasks and investigated how emotional–social-related hotel robots influence consumers’ intention to stay at robot hotels.

The lack of appropriate animal models reflecting human disease conditions and poorly understood disease mechanisms increase the difficulty of drug development using preclinical models focused on specific molecular mechanisms in psychiatric diseases. Therefore, drug repurposing approaches are widely used for the development of psychiatric drugs. This chapter discusses the drug repurposing strategies used for psychiatric drug development and the concepts realized through them. Additionally, it highlights the drugs developed using drug repurposing approaches and approved for psychiatric disease treatment in the United States in the past 20 years. This chapter also summarizes the success of recent drug repurposing strategies for psychiatric diseases in the late clinical development stage. Overall, this chapter describes the practical use of drug repurposing for psychiatric drug development.