In an era of intensified market competition, internal brand management (IBM) has emerged as a critical strategy for aligning employee behavior with brand values. This study investigates how IBM influences brand citizenship behavior (BCB) among front-line restaurant employees in Macao, emphasizing the mediating role of brand identification (BI) and simultaneously testing the moderating effect of leader-member exchange (LMX). Drawing from Social Identity Theory and Social Exchange Theory, the structural equation modeling (SEM) was used to test the model using data from 315 employees across 11 Macao restaurant companies. Analyzing via software package Smart-Pls 4.1, we found that IBM significantly enhances BI, which in turn strongly predicts BCB. While IBM directly impacts BCB, the effect is mediated by BI. Furthermore, LMX moderates the IBM-BI relationships, underscoring the role of leadership in internal branding effectiveness. These findings contribute to the internal branding literature by validating BI as a key psychological mechanism and LMX as a boundary condition. Practically, the study provides insights for restaurant industry seeking to foster brand-aligned behaviors through internal brand management.
The rapid development of cities and urbanization in China has forced the growth of new channels for buying agricultural products. The purpose of this research is to examine how Internet of Things (IoT’s) technologies can digitize a traditional fresh food supply chain. Comparative and descriptive analysis methods are used to highlight the major pain points in the traditional supply chains and assess how digital transformation could help. We delve into every part of digital transformation, which includes establishing an information platform based on IoT and developing smart storage options. Our findings revealed that through end-to-end digital integration, supply chain efficiency is improved with shorter lead times and leaner inventories that yield reduced costs as well as fewer losses while ensuring product quality and traceability. In sum, such an approach would enhance sustainability within the fresh food value chain. As such, our article highlights key aspects of transitioning towards a digital environment in this sector for those planning similar ventures.
Cyclically, the debate on Keynes’ economic policies reemerge. The economic impact of the pandemic caused by COVID-19 has relaunched the discussion about the importance of Keynesian policies, the multipliers effects, and their impact on stimulating economies. This paper aims to analyze the importance and relevance of the Keynesian multiplier before the pandemic, in a period without experiencing exceptional aggregate shocks. The main focus of the research is to examine the shortcomings of the public investment multiplier, which plays a central role in Keynesian theory. Despite the undeniable relevance of the concept, the issue is to understand the extent to which the multiplier is still relevant in specific contexts. The research presents empirical evidence which suggests that the effects of public investment depend on structural characteristics of economies specifically trade liberalization, the dimension of internal markets, the question of countries having the freedom to issue their currency, and the issue of currencies being accepted as an international reserve. A sample of 35 OECD countries was used for the period 2010–2018. The Keynesian public investment multiplier was calculated for several countries and the obtained values were related to various correlations carried out to assess the relationship between public investment, national income, and specific characteristics of the economies to which the multipliers are sensitive. The results obtained contrast in terms of short-term and long-term impacts so, is at least dubious, that one can rely on Keynesian public policies to boost economies at least in the absence of substantial shocks to aggregate demand.
The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.
The use of autonomous weapons systems (AWS) has led to several opposing legal opinions regarding their violations of international law. The responsibility of the state, individuals, and corporations as producers, designers, and programmers is all being taken into consideration. If the decision to kill humans without “meaningful human control” is transferred to computers, it would be hard to attribute accountability for the actions of AWS to their corporations. Consequently, this means that corporate actors will enjoy impunity in all cases. The present paper indicates that the most significant problem arising from the use of AWS is the attribution of responsibility for its violation. Corporations are not subject to liability for the legitimate use of weapons under international law. The main problem with corporate responsibility, according to article 25 (4) of the Rome Statute, is that the provision only relates to individual criminal responsibility and that the ICC shall only have jurisdiction over natural persons. Nevertheless, corporations may be held accountable under aspects of international law. The paper proposes a more positive view on artificial intelligence, raising corporations’ accountability in international law by historically linking the judging of business leaders. The article identifies aiding and abetting as well as co-perpetration as the two modes of accountability under international law potentially linked to AWS. The study also explores the main ambiguity in international law relating to corporate aiding and abetting of human rights violations by presenting the confusion on determining the standards of these 2 modes of liability before the ICC and International ad doc Tribunal. Moreover, with the new age of war heavily dependent on AI and AWS, one cannot easily and precisely ascertain who must be held accountable for war crimes because of the unanticipated facts in decision-making combined with the aiding or abetting of violations of international law. International law prioritizes the goal of ending impunity for the individual and largely neglects the need to achieve the same goal for corporate complicity. In sum, progress to regulate the use of AWS by corporate actors could be enormously helpful to the cause of ending impunity.
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