Search Results (198)

Research Problem and Gap: Live streaming sales rely heavily on streamers, with both genuine and AI-generated virtual streamers gaining popularity. However, these streamer types possess contrasting capabilities. Genuine streamers are superior at building trust and reducing product valuation uncertainty but have limited reach, while virtual streamers excel at broad audience engagement but are less effective at mitigating uncertainty, often leading to higher product return rates. This trade-off creates a critical strategic gap; that is, brand firms lack clear guidance on whether to invest in genuine or virtual streamers or adopt a hybrid approach for their live channels. Objective and Methods: This study addresses this gap by developing a theoretical analytical model to determine a monopolistic brand firm’s optimal streamer strategy among three options: using only a genuine streamer, only a virtual streamer, or a combination of the two (hybrid approach). The researchers model consumer utility, factoring in uncertainty and the streamers’ differential impact on reach, to derive optimal decisions on pricing and streamer selection. Results and Findings: The analysis yields several key findings with direct managerial implications. First, while a hybrid strategy leverages the complementary strengths of both streamer types, its success depends on employing high-quality streamers; in other words, this strategy does not justify settling for inferior talent of either type. Second, employing a virtual streamer requires a moderate price reduction to compensate for higher consumer uncertainty and prevent high profit-eroding return rates. Third, a pure strategy (only genuine or only virtual) is optimal only when that streamer type has a significant cost advantage. Otherwise, the hybrid strategy tends to be the most profitable. Moreover, higher product return costs directly diminish the viability of virtual streamers, making a genuine or hybrid strategy more attractive for products with expensive return processes. Conclusions: The results provide a clear framework for brand firms—that is, the choice of streamer is a strategic decision intertwined with pricing and product return costs. Firms should pursue a hybrid strategy not as a compromise but as a premium approach, use targeted pricing to mitigate the risk of virtual streamers, and avoid virtual options altogether for products with high return costs. Full article

This paper presents a comprehensive analysis of the border city of Jilong in Tibet, China, within the wider context of the global south and the transformation of China’s interior frontier in recent decades. It examines the transformation process of Jilong, identifies the driving factors of its development, and investigates the implementation and impact of relevant policies. Employing a longitudinal case study method, semi-structured interviews, and multi-source data analysis (including policy documents, statistical bulletins, and field notes), this research examines Jilong’s transformation trajectory, the factors behind this change, and policy implementation outcomes. The findings reveal that Jilong has undergone a significant transition from a traditional border trade point to a national strategic hub. Industrial diversification, infrastructure modernization, and governance innovation are recognized as central to this transformation. Additionally, the study also finds challenges such as ecological vulnerability, geological disaster risk, and the necessity for enhancement in cross-border collaboration mechanisms, proposing measures like green development, customs facilitation, and a system for both importing and cultivating local talent. This research emphasizes the transformation of border cities from a complex interplay of national strategy, external shocks, and local initiative. It accordingly advocates for an integrated development model, which combines policy empowerment, resilient infrastructure, cultivation of distinctive industries, and refined border governance. This study adds to research on border cities in the Global South and provides insights for supporting sustainable development in similar cities located in strategic corridors. Full article

In the context of the digital economy reshaping the global competitive landscape, digital industry clusters have become the key driving force to overcome the diminishing returns of traditional inputs and realize sustainable economic development in the digital era. However, the internal mechanisms and spatial effects through which digital industrial clusters drive high-quality development and thereby foster sustainable regional economic growth remain unclear. Based on China’s provincial panel data from 2012 to 2023, this study constructs time-fixed spatial Durbin model and mediation effect model to systematically examine the impact mechanism of digital industry clusters on high-quality economic development, and to analyze their direct effects, spatial spillover effects and mediation transmission effects. The following effects have been found: (1) digital industry clusters can directly promote the high-quality development of the region’s economy (0.070), and can also significantly promote the high-quality development of the region’s economy through the mediating effect of innovative talent agglomeration (0.021); (2) the spatial spillover effect of digital industry clusters consists of the negative siphoning effect of innovative talent and positive technology diffusion and driving effect, which makes the total effect of digital industry clusters on neighboring regions uncertain; (3) Technology-intensive areas, as well as the eastern and northeastern regions, have effectively transformed the advantages of digital industry clusters into momentum for high-quality economic development, whereas central and western regions have not yet fully unleashed the driving effect of digital industry on the high-quality development of the economy, due to the constraints of the industrial structure, innovation factors and infrastructure. Based on the empirical results, the article suggests accelerating the construction of digital industry innovation hubs, establishing cross-regional technology sharing platforms, constructing a negative externality compensation mechanism for talent loss areas, and implementing differentiated regional development strategies. The study addresses a gap in existing research by analyzing the spatial mediation effects of digital industrial agglomeration on high-quality economic development. It extends theoretical insights into industrial clustering within the digital economy and offers actionable policy pathways for developing countries to promote sustainable economic growth through digital industrial clusters. Full article

I recently developed the concept of eco-cognitive openness and situatedness to explain how cognitive systems, whether human or artificial, engage dynamically with their surroundings to generate information and creative outcomes through abductive cognition. Human cognition demonstrates significant eco-cognitive openness, utilizing external resources like tools and cultural contexts to produce contextually rich hypotheses, sometimes highly creative via what I called “unlocked strategies.” Conversely, generative AI, such as large language models (LLMs) and image generators, employs “locked strategies,” relying on pre-existing datasets with minimal real-time environmental interaction—this leads to limited creativity. While these systems can yield some low-level degrees of creative outputs, their lack of human-like eco-cognitive openness restricts their ability to achieve high-level creative abductive feats, which remain a human strength, especially among the most talented. However, LLMs often outperform humans in routine cognitive tasks, exposing human intellectual limitations rather than AI deficiencies. Much human cognition is repetitive and imitative, resembling “stochastic parrots,” much like LLMs. Thus, LLMs are potent cognitive tools that can enhance human performance but also endanger creativity. Future AI developments, such as human–AI partnerships, could improve eco-cognitive openness, but risks like bias and overcomputationalization necessitate human oversight to ensure meaningful results. In collaborative settings, generative AI can serve as an epistemic mediator, narrowing the gap toward unlocked creativity. To safeguard human creativity, control over AI output must be maintained, embedding them in socio-cultural contexts. I also express concern that ethical and legal frameworks to mitigate AI’s negative impacts may fail to be enforced, risking “ethics washing” and “law washing.” Full article

Against the background of China’s ecological civilization construction and sustainable development strategies, how remote sensing courses adapt to the demands of the artificial intelligence era has become an urgent issue for undergraduate education in relevant disciplines at universities. This study proposed a trinity teaching reform path of “deep learning and remote sensing, and ecological sustainability”, aiming to cultivate interdisciplinary talents with capabilities in intelligent interpretation and practical application. The study established a three-stage curriculum objective system, integrating knowledge, ability, and literacy, designed a five-dimensional linkage teaching method combining case-driven teaching, modular training, and blended learning, and conducted teaching practices using mainstream deep learning frameworks and cloud platforms. Through hierarchical teaching practice cases and multi-dimensional evaluation data, it was shown that the reform effectively enhanced the experiment group students’ abilities in deep learning applications, complex remote sensing data processing, and ecological problem-solving. The achievement values for all five evaluation indicators exceeded 80%, with the highest improvement reaching 28% compared to the control group. The results indicate that this teaching reform not only enhances learning outcomes but also provides a valuable framework and practical pathway for remote sensing education empowered by artificial intelligence and the cultivation of professional talent in future sustainable development fields. Full article

The development of E-commerce and digitalization drives the rapid change in logistics management practices and poses challenges to traditional talent training modes in logistics field. Nowadays, companies expect university graduates equipped with more practical logistics skills to connect tighter with the industry. This motivates universities to establish more practically relevant curriculums to enhance students’ career competitiveness. Under such background, industry–university collaboration courses are increasingly adopted in higher education institutes in logistics discipline. Due to the difference between this type of course and the traditionally taught courses, the learning outcome of it can be difficult to guarantee. Therefore, it is necessary to identify the influential factors of the learning outcomes of industry–university collaboration courses and establish the actionable strategies to enhance course quality. However, the current literature in logistics management education has little focus on this topic, resulting in gaps on clarifying the influential factors of learning outcomes of industry–university collaboration courses in this discipline. Applying a mixed method, this study conducted a case study for an industry–university collaboration course of a logistics discipline in a Chinese university. The interval-valued Pythagorean fuzzy (IVPF) numbers and the Weighted Aggregated Sum Product Assessment (WASPAS) methods were used. The results showed that there are 15 factors which can influence the outcomes of industry–university collaboration courses in logistics discipline. Among them, the most important factor is the working environment, followed by the students’ own ability. Also, the results indicated that students’ optimistic attitudes towards the course, whether students take the course seriously, and course evaluations can be influential factors for good learning outcomes. The sensitivity analysis was then conducted, showing that the results were robust. This study can contribute to the existing literature by providing a theoretical framework to understand and assess the quality of industry–university collaboration courses in logistics and relevant subjects, as well as offering new analytical tools for management educational studies. Moreover, this study can provide practical implications for educators to develop and maintain good industry–university collaboration courses and trainings. Specifically, a practical life-cycle view was suggested to put pertinent efforts in all periods before/during/after the course to achieve high course outcomes. Full article

To mitigate persistent urban–rural disparities and facilitate comprehensive rural development, the Chinese government institutionalized the Rural Revitalization Strategy. This national policy framework systematically addresses five critical domains of rural development: (1) industrial revitalization, (2) talent revitalization, (3) organizational capacity building, (4) cultural heritage preservation, and (5) ecological conservation. Among them, talent cultivation serves as both a fundamental objective and critical resource for the sustainable rural economic transformation. However, the existing research and practice have disproportionately emphasized industrial and ecological aspects, largely neglecting the acute talent shortage. This study bridges this gap by adopting a population mobility lens to categorize young talent types contributing to Chinese rural economic transformation and analyze their mobility trajectories and resource exchange dynamics. Drawing on an integrated theoretical framework combining Push–Pull Theory and Existence–Relatedness–Growth Theory, as well as empirical evidences from Yuan Village in Shaanxi Province, this research has four key findings. First, there are three distinct young talent categories that have emerged in Chinese rural economic transformation: urban-to-rural young talents, native young talents, and rural-to-rural young talents. It is noteworthy that the rural-to-rural young talent represents a novel flow pattern that can expand our conventional understandings of Chinese population mobility. Second, differential push–pull factors shape each category’s migration decisions, subsequently influenced by their existence needs, social relatedness, and growth requirements as outlined in ERG Theory. Third, through heterogeneous resource exchanges with villagers, committees, and communities, these talents negotiate their positions and satisfy their expectations within the rural socio-economic system. Fourth, unmet exchange expectations may precipitate talent outflow, which will further pose sustainability challenges to revitalization efforts. Additionally, the long-term impacts of the intensified social interactions between talent groups and local residents, as well as their generalizability, require further examination. Full article

This study explores the migration intentions of university students—representing the potential creative class—in Erzurum, a medium-sized city in eastern Turkey experiencing shrinkage. Within the theoretical framework of shrinking cities, it investigates how economic, social, physical, and personal factors influence students’ post-graduation stay or leave decisions. Survey data from 742 Architecture and Fine Arts students at Atatürk University were analyzed using factor analysis, logistic regression, and correlation to identify key migration drivers. Findings reveal that, in addition to economic concerns such as limited job opportunities and low income, personal development opportunities and social engagement also play a decisive role. In particular, the perception of limited chances for skill enhancement and the belief that Erzurum is not a good place to meet people emerged as the strongest predictors of migration intentions. These results suggest that members of the creative class are influenced not only by economic incentives but also by broader urban experiences related to self-growth and social connectivity. This study highlights spatial inequalities in access to cultural, educational, and social infrastructure, raising important questions about spatial justice in shrinking urban contexts. This paper contributes to the literature on shrinking cities by highlighting creative youth in mid-sized Global South cities. It suggests smart shrinkage strategies focused on creative sector development, improved quality of life, and inclusive planning to retain young talent and support sustainable urban revitalization. Full article

With deepening global higher education reforms, outcome-based education has emerged as the core paradigm for teaching model innovation. This study investigates the structural dependencies and teaching effectiveness of the Environmental Design curriculum at Hubei Engineering University in medium-sized cities, China, addressing challenges of enrollment decline and market contraction critical for urban sustainability. Using network analysis, we construct curriculum support and contribution networks and course temporal networks to assess structural dependencies and teaching effectiveness, revealing structural patterns and optimizing the OBE-based Environmental Design curriculum to enhance educational quality and student competencies. Analysis reveals computer basic courses as knowledge transmission hubs, creating a course network with a distinct core–periphery structure. Technical course reforms significantly outperform theoretical course reforms in improving student performance metrics, such as higher average scores, better grade distributions, and reduced performance gaps, while innovative practice courses show peripheral isolation patterns, indicating limited connectivity with core curriculum modules, which reduces their educational impact. These findings provide empirical insights for curriculum optimization, supporting urban sustainable development through enhanced professional talent cultivation equipped to address environmental challenges like sustainable design practices and resource-efficient urban planning. Network analysis applications introduce innovative frameworks for curriculum reform strategies. Future research expansion through larger sample validation will support urban sustainable development goals and enhance professional talent cultivation outcomes. Full article

This study explores the role of artificial intelligence (AI) in human resource management (HRM), with a focus on recruitment, employee retention, and performance optimization. Through a PRISMA-based systematic literature review, the paper examines many machine learning algorithms including XGBoost, SVM, random forest, and linear regression in decision-making related to employee-attrition prediction and talent management. The findings suggest that these technologies can automate HR processes, reduce bias, and personalize employee experiences. However, the implementation of AI in HRM also presents challenges, including data privacy concerns, algorithmic bias, and organizational resistance. To address these obstacles, the study highlights the importance of adopting ethical AI frameworks, ensuring transparency in decision-making, and developing effective integration strategies. Future research should focus on improving explainability, minimizing algorithmic bias, and promoting fairness in AI-driven HR practices. Full article

The present research examines the intersections of giftedness, disability status, and cultural identity through the case of Kent, a nine-year-old Asian American boy who is not only profoundly gifted but has also been diagnosed with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and possibly developmental coordination disorder (DCD). This study offers a comprehensive exploration of how these overlapping factors shape Kent’s early talent development and educational experiences, while also highlighting the challenges faced by his family and their need for a personalized, holistic support system tailored to his unique combination of abilities and disabilities. While Kent’s case is not generalizable, it underscores the critical importance of understanding the dynamic interplay among giftedness, disability status, and cultural identity in developing effective educational strategies. Furthermore, we advocate for personalized interventions that extend beyond conventional approaches, such as applied behavior analysis (ABA), to adequately address the complex needs of multi-exceptional individuals like Kent. Full article

Introduction: Poorly designed safety job descriptions may have a negative impact on occupational safety and health (OSH) performance. Firstly, they limit the chances of hiring highly qualified safety professionals who are vital to the success of OSH management systems in organizations. Secondly, the relationship between the presence of qualified safety professionals and the safety culture (and performance) in an organization is reciprocal. Thirdly, the low quality of job descriptions limits exploring the proper competencies needed by safety professionals before they are hired. The safety professional is thus uncertain of what level of education or training and which skills they should attain. Objectives: The main goal of the study is to integrate the analytic hierarchy process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with importance–performance analysis (IPA) to evaluate job descriptions in multiple sectors. Results: The results of the study indicate that it is vital to clearly define job levels, the overall mission, key responsibilities, time-consuming tasks, required education/certifications, and necessary personal abilities in safety job descriptions. This clarity enhances recruitment, fairness, performance management, and succession planning. The organization can then attract and retain top talent, improve performance, foster a strong safety culture, create realistic job expectations, increase employee satisfaction and productivity, and ensure that competent individuals are hired, ultimately leading to a safer and more productive workplace. Conclusion: The outcomes of this study provide a robust framework that can and should be used as a guideline to professionalize job description development and enhance talent acquisition strategies. Full article

The rapid rise of the silver economy in the new era has become a new driving force for socio-economic development. From the perspective of Marxist political economy theory, this paper analyzes the intrinsic logic of the silver economy’s development through three dimensions: surplus value, labor market, and capital. The study finds that the silver economy in the new era faces challenges such as insufficient supply of high-quality elderly care services, simultaneous shortages in both total talent quantity and structural imbalances, and contradictions between capital’s profit-seeking nature and social welfare. By introducing the multiple streams model, the paper elucidates the coupling process of these three streams and the timing of policy window openings. It proposes targeted strategies, including strengthening technological innovation, deepening labor market reforms, and optimizing capital allocation, to promote the robust development of China’s silver economy and inject strong momentum into sustainable and high-quality economic growth. Full article

In order to cope with the multimodal changes led by the digital era, enterprises urgently need to promote the construction of new-quality productive forces (NQPFs) through digital transformation. NQPFs take digital technology empowerment as the core driving force and emphasize the dynamic matching and synergy between the new-quality elements (digital infrastructure, digital talents, data resources, and diversified ecology) and the new-quality capabilities (digital dynamic capabilities) so as to unleash the innovation potentials of different production modes. Based on resource orchestration theory, this study constructs a “resource-capability-value creation” framework for digital empowerment (D-RCV) and employs fuzzy set qualitative comparative analysis (fsQCA) to examine 205 enterprise samples. Results reveal that enhanced innovation performance stems from digital empowerment at both resource and capability levels, generating three configurational paths: collaborative symbiosis, resource optimization, and data-driven approaches. These paths emerge through the interaction of resources and capabilities under different conditions. This study contributes by proposing a digital empowerment framework and exploring multiple pathway choices for new-quality productivity development. The findings provide theoretical insights for enterprise innovation research and practical guidance for innovation management strategies. Full article

This study investigates the cybersecurity landscape of Aotearoa-New Zealand through a culturally grounded lens, focusing on the integration of Indigenous Māori values into cybersecurity frameworks. In response to escalating cyber threats, the research adopts a mixed-methods and interdisciplinary approach—combining surveys, focus groups, and case studies—to explore how cultural principles such as whanaungatanga (collective responsibility) and manaakitanga (care and respect) influence digital safety practices. The findings demonstrate that culturally informed strategies enhance trust, resilience, and community engagement, particularly in rural and underserved Māori communities. Quantitative analysis revealed that 63% of urban participants correctly identified phishing attempts compared to 38% of rural participants, highlighting a significant urban–rural awareness gap. Additionally, over 72% of Māori respondents indicated that cybersecurity messaging was more effective when delivered through familiar cultural channels, such as marae networks or iwi-led training programmes. Focus groups reinforced this, with participants noting stronger retention and behavioural change when cyber risks were communicated using Māori metaphors, language, or values-based analogies. The study also confirms that culturally grounded interventions—such as incorporating Māori motifs (e.g., koru, poutama) into secure interface design and using iwi structures to disseminate best practices—can align with international standards like NIST CSF and ISO 27001. This compatibility enhances stakeholder buy-in and demonstrates universal applicability in multicultural contexts. Key challenges identified include a cybersecurity talent shortage in remote areas, difficulties integrating Indigenous perspectives into mainstream policy, and persistent barriers from the digital divide. The research advocates for cross-sector collaboration among government, private industry, and Indigenous communities to co-develop inclusive, resilient cybersecurity ecosystems. Based on the UTAUT and New Zealand’s cybersecurity vision “Secure Together—Tō Tātou Korowai Manaaki 2023–2028,” this study provides a model for small nations and multicultural societies to create robust, inclusive cybersecurity frameworks. Full article