Search Results (1,983)

This study aims to systematically reveal, from the perspective of organizational scale, the differences between large and small architectural design organizations in China in terms of characteristics of production activities, technological capabilities and innovation levels, resource integration capabilities, and client groups, and to quantify the priority order of clients’ attention to architectural design products, thereby providing a reference for industry structure optimization and strategic decision making. This research combines case analysis and comparative study to construct a four-dimensional comparative framework. The results show that large design organizations, leveraging their advantages in technological research and development as well as resource integration, focus on large-scale complex projects, technology-driven projects, cultural landmark projects, and multi-stakeholder collaborative projects, primarily serving government agencies and large enterprises. In contrast, small design organizations excel in flexibility, concentrating on small-scale simple projects, specialized niche projects, localized projects, and short-cycle, low-budget projects, serving individual owners and small businesses. Furthermore, this study adopts the Analytic Hierarchy Process (AHP) to establish an evaluation model. Twenty experts from architectural design organizations, construction organizations, and research institutions were invited to score the survey questionnaires, and quantitative weight analysis was performed. The research findings provide support for the optimization of the industry. Full article

Aim: This study extends existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often overlooked group of stakeholders in the adoption of new technologies within the hotel sector. The objective of this research is to investigate the perceptions of hotel employees in Hong Kong regarding the implementation of Metaverse hotels. This study emphasizes their evaluations of the strengths, weaknesses, opportunities, and threats associated with these establishments through a SWOT analysis. Ultimately, the study aims to provide recommendations for addressing technological challenges, supporting employees during the transition, and facilitating adaptation across the industry. Design/Methodology/Approach: A convenience and purposive sampling method is employed to investigate 20 participants, comprising hotel staff from various departments in the Metaverse hotel in Hong Kong. This study adopts a qualitative research design, utilizing semi-structured interviews to gather in-depth insights into the perceptions of the Metaverse hotel among these employees. Purposive sampling ensures that participants have relevant experience and familiarity with VR/AR technologies. Interviews, each lasting 45–60 min, were conducted in person, with informed consent obtained beforehand. Findings: The exploration of hotel employees’ perceptions of Metaverse hotels in Hong Kong underscores the innovative potential of these establishments to enhance operational efficiency and guest engagement, while also offering new training opportunities and streamlining daily tasks. However, employees express concerns about the potential erosion of personal interactions, which are crucial to the hospitality experience, and foresee significant technical and integration challenges. Despite these drawbacks, Metaverse hotels present distinctive opportunities for market differentiation, appealing to tech-savvy guests and generating new revenue streams that contribute to industry growth. Nonetheless, potential threats such as guest skepticism and challenges in industry adaptation highlight the necessity for cautious implementation and robust privacy measures. Balancing these aspects—strengths, weaknesses, opportunities, and threats—will be pivotal for the successful integration of Metaverse technologies into the hotel industry. Theoretical/Practical Implications: Participants recognized that the Metaverse hotel could offer various potential benefits for both employees and businesses, such as enhanced operational efficiencies and new opportunities for guest engagement. Understanding the perceptions of hotel staff towards the Metaverse carries significant real-world implications for shaping policies, practices, and technologies that facilitate its operational success and market acceptance. Leveraging these insights enables the optimization of Metaverse’s advantages while mitigating associated risks and drawbacks. This study advances existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often neglected group of stakeholders in the adoption of new technologies within the hospitality sector. By understanding the perspectives of hotel employees, this research provides valuable insights into the practical challenges and benefits of implementing Metaverse technologies in the hotel industry. Originality/Value: The Metaverse hotel is still relatively new and evolving, making it crucial to conduct research to understand how hotel staff perceive it. However, there is limited research specifically focusing on the perceptions of hotel employees regarding Metaverse hotels. This gap highlights the need for a comprehensive investigation into how employees perceive the strengths, weaknesses, opportunities, and threats of implementing the Metaverse in hotels. Full article

Cultivating the best business environment ecosystem is important for advancing market-oriented reforms and achieving sustainable industrial transformation. How to quantify the business environment is also a relatively complex topic. Based on urban ecology theory, this study constructs a comprehensive evaluation framework for assessing urban business environment development. Using the entropy weight method and spatial autocorrelation analysis, we examine the time series and spatial evolution of the business environment in the Guangdong–Hong Kong–Macao Greater Bay Area from 2008 to 2021. Meanwhile, we further explore the main factors that influence the development level of the business environment. Finally, some suggestions are put forward to improve the business environment. The results show that (1) the development level of the business environment has gradually improved during the sample period, with stable growth from 2008 to 2015, followed by rapid development after 2015; (2) from different dimensions, there is an imbalance in the business environment development among cities within the Greater Bay Area, with core cities performing better than others; (3) from a spatial perspective, the business environment presents a “core-periphery” pattern, with higher levels clustered around the Pearl River Estuary, indicating strong spatial agglomeration. This research provides theoretical support and policy recommendations for the Three-Year Action Plan for Creating a World-Class Business Environment in the Greater Bay Area. Full article

Customer segmentation is a foundation of Customer Relationship Management (CRM) and is widely regarded as a key to business development success. As the principles of sustainable development become increasingly central to business strategy, it is necessary that social, environmental, and economic considerations be incorporated into customer segmentation—even in regulated markets such as the postal market. The article develops and applies a three-dimensional (3D) segmentation model of business customers in the Slovak postal market, utilizing cluster analysis within STATISTICA analytical software for operationalization of the segmentation criteria. The 3D model reacts to the three pillars of sustainable development and is verified under real conditions at Slovak Post, plc. By adopting a systems perspective, the research places customer segmentation as an integral component of the entire socio-technical system, emphasizing the interrelatedness of organizational, social, and environmental considerations. The study illustrates how a systems-based approach to segmentation enables postal operators to uncover key customer segments, optimize resource allocation, and support competitiveness and sustainability goals. The practical applicability of the model is illustrated by its potential for application in other regulated service industries, providing a solid framework for sustainable customer management and strategic decision-making in complex environments. The research underscores the critical role of systems thinking in addressing the complex challenges of sustainable development in regulated industries. Full article

In response to increasing global sustainability demands, this study examines how green dynamic capabilities influence business performance in Bali Island’s tour and travel SMEs, with green service innovation as a mediating mechanism. Drawing on the resource-based view (RBV) and dynamic capability theory, the research adopts a quantitative approach using survey data from 387 SMEs and employs structural equation modeling (SEM) to analyze the relationships among green dynamic capabilities, green service innovation, and business performance. Findings reveal that green dynamic capabilities significantly enhance both green service innovation and business performance. Notably, green service innovation partially mediates this relationship, underscoring its pivotal role in transforming internal sustainability-oriented capabilities into tangible performance outcomes. The key contribution of this study lies in extending RBV by integrating green service innovation as a strategic conduit that links eco-centric capabilities to competitive advantage in a tourism SME context—a perspective that remains underexplored in emerging economies. Practically, the study provides actionable insights for SME owners and policymakers to prioritize innovation in service design and delivery as a pathway to sustainable tourism performance. Full article

This article presents an analysis of a logistics process using process mining methods. Additionally, it highlights the possibilities of analyzing industrial process data using the process mining tools available in the ProM software 6.12. The paper explains what process mining is, its types and perspectives, and its potential applications in business process management. This analysis is based on an event log, while the process model is presented in the form of a Petri net. The process research was carried out using ProM software and its available tools. The dataset is characterized, and the results of the conducted studies are presented, including an analysis of the event log, process flow network analysis, and conformance checking between the model and the event log, as well as time-based, organizational, and error detection analyses. Solutions to the identified problems are proposed. In summary, this article presents an analysis of a logistics process that was generated based on system process data, and demonstrates the possibilities of using selected algorithms from the ProM software. Full article

Emerging technologies present significant challenges for society as a whole. Among these, Artificial Intelligence (AI) stands out for its transformative potential, with the capacity to fundamentally reshape human thought, behavior, and lifestyle. This article seeks to explore the business-oriented perspective on how AI should be approached in Higher Education (HE) in order to serve the commercial objectives of companies. The motivation for this inquiry stems from recurrent criticisms directed at HE institutions, particularly their perceived inertia in adopting innovations, resistance to change, and delayed responsiveness to evolving labor market demands. In this context, the study examines what businesses deem essential for universities to provide in the context of AI familiarity and examines how companies envision future collaboration between the business sector and Higher Education institutions in using AI for business applications. Adopting a qualitative research methodology, this study conducted interviews with 16 middle-management representatives from international corporations operating across diverse industries. The data were analyzed using Gioia’s methodology, which facilitated a structured identification of first-order concepts, second-order themes, and aggregate dimensions. This analytical framework enabled a nuanced understanding of business expectations regarding the role of HE institutions in preparing graduates capable of meeting economic and commercial imperatives under the pressure of AI diffusion. Full article

China’s rapid urbanization has presented challenges for sustainably revitalizing the historic and cultural heritage within its urban villages. Often, these efforts overlook the crucial roles of community ties and cultural values. This study focuses on 15 representative urban villages in Guangzhou (2019–2024). It tests the core idea that the physical layout of these spaces reflects underlying community structures and cultural values shaped by specific policies. Integrating this understanding into landscape planning can significantly improve revitalization outcomes. We used a mixed-methods approach: (1) Extended fieldwork to understand community networks and cultural practices; (2) Spatial analysis to measure how building density relates to land uses; (3) Sentiment analysis to reveal how people perceive cultural symbols; (4) A coordination model to link population influx with landscape suitability. Key findings reveal different patterns: Villages with strong clan networks maintained high cultural integrity and public acceptance through bodies like ancestral hall councils. Economically driven villages showed a split—open for business but culturally closed, with very low tenant participation. Successful revitalization requires balancing three elements: protecting physical landmarks in their original locations; modernizing cultural events; and reconstructing community narratives. Practically, we propose a planning framework with four approaches tailored to different village types. For instance, decaying villages should prioritize repairing key landmarks that hold community memory. Theoretically, we build a model linking social and spatial change, extending the cultural value concepts of Amos Rapoport to the context of fast-growing cities. This provides a new methodological perspective for managing urban–rural heritage in East Asia. Full article

In recent years, a significant shift has occurred regarding the role of businesses in achieving sustainable development. This evolving perspective emphasizes a systems thinking approach to business operations, advocating for the transformation of business models to support the restoration and regeneration of natural resources and social systems. This study aims to explore and analyze the scholarly contributions that investigate the role of businesses as an agent of positive impact and growth. Adopting bibliometric systematic literature review (B-SLR) protocols and tools, a solid theoretical framework for regenerative business models (RBMs) is established, contributing to the ongoing discourse on the definition and operationalization of regeneration in business contexts. Using specific inclusion and exclusion criteria in PRISMA flow diagram for SLR, 151 research articles from the Scopus database were deemed eligible for analysis. Co-occurrence analysis with VOSviewer 1.6.8 identified only 10 scholarly papers with conceptual linkages and thematic convergence related to RBMs, providing insights in the field and offering a strong exploratory tool for visualizing and examining the intellectual structure of this scientific area. Subsequently, a content analysis was conducted, to reveal thematic patterns and research trends within the identified clusters. The findings provide valuable insights for both practitioners—by informing strategic decision-making—and academics—by highlighting research progress and outlining future avenues for inquiry to address existing gaps in the literature. Full article

Career decisions are among the most consequential choices individuals make, profoundly shaping their long-term stability and overall life satisfaction. The literature suggests that behavioral biases, specifically overconfidence, herd mentality, social comparison, status quo bias, and optimism bias, can exert considerable influence on these decisions, thereby shaping students’ future career trajectories. This study adopts a behavioral perspective to examine how these biases influence career choices within a collectivist social context. A survey of 360 undergraduate and graduate business students was conducted. The collected data were analyzed using an integrated approach that combines Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN), enabling the use of both linear and non-linear methods to analyze the relationship between cognitive biases and career choices. Our findings reveal that while all five biases have a measurable impact, status quo bias and social comparison are the dominant factors influencing students’ career decisions. These results underscore the need for interventions that foster self-awareness, independent decision-making, and critical thinking. Such insights can guide educators, career counselors, and policymakers in designing programs to mitigate the negative effects of cognitive biases on career decision-making, ultimately enhancing career satisfaction and workforce efficiency. Full article

The purpose of this study was to analyze the impact of organizational culture on knowledge management in public elementary, secondary, and middle schools in the department of Caquetá, Colombia, based on the perceptions of managers, teachers, and administrative staff. A quantitative and correlational scope approach methodology was applied through a confirmatory factor analysis based on the use of structural equations in the SMARPLS software versión 4.0.9.7. The population under study comprised teachers, managers, and administrative staff, with a total of 362 respondents belonging to these public educational institutions. Evaluating the fundamental components of the studied constructs made it possible to show the significant influence of organizational culture on knowledge management, in which a well-structured culture takes institutional objectives that improve the processes of the creation, storage, and dissemination of knowledge into account, thus ensuring the sustainability and operational efficiency of the institution. In the specific context of the education sector, the impact and contributions of this research can be significant and timely for planning educational management in public elementary, secondary, and middle schools based on the recognized importance of knowledge management for public policy. In addition, educational institutions can be studied using theories that are usually applied in the business context, thus enhancing replicability, not only from the perspectives of education and pedagogy but also from an administrative point of view. Full article

This study intends to provide insights and challenges for the shape of the B movement, an emerging paradigm that fosters cross-sectoral partnerships and encourages ethical business practices through so-called purpose-driven businesses. Focusing on Italy, the first European country to adopt this managerial model, the research investigates Italian Benefit Corporations, known as Società Benefit (SB), and their most appealing sustainability claims from a consumer perspective. The analysis intends to inform theory development by assuming the cultural and creative industry (CCI) as a field of interest, utilizing a within-subjects experimental design to analyze data from a diverse consumer sample across various contexts. The results indicate that messaging centered on economic sustainability emerged as the most effective in generating positive consumer responses, highlighting a prevailing inclination toward pragmatic factors such as affordability, economic accessibility, and tangible benefits rather than social issues. While sustainable behaviors are not yet widespread, latent ethical sensitivity for authentic, value-driven businesses suggests that economic and ethical dimensions can be strategically synthesized to enhance consumer engagement. This insight highlights the role of BCs in catalyzing a shift in consumption patterns within ethical-based and creative-driven sectors. Full article

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

The sharing economy is considered to be a potentially efficacious approach for promoting sustainable production and consumption (SPC). This study utilizes dockless bike sharing (DBS) in Beijing as a case study to examine how sharing economy policies and business practices advance SPC. It also dynamically quantifies the environmental and economic performance of DBS practices from a life cycle perspective. The findings indicate that effective SPC practices can be achieved through the collaborative efforts of multiple stakeholders, including the government, operators, manufacturers, consumers, recycling agencies, and other business partners, supported by regulatory systems and advanced technologies. The SPC practices markedly improved the sustainability of DBS promotion in Beijing. This is evidenced by the increase in greenhouse gas (GHG) emission reduction benefits, which have risen from approximately 35.81 g CO₂-eq to 124.40 g CO₂-eq per kilometer of DBS travel. Considering changes in private bicycle ownership, this value could reach approximately 150.60 g CO₂-eq. Although the economic performance of DBS operators has also improved, it remains challenging to achieve profitability, even when considering the economic value of the emission reduction benefits. In certain scenarios, DBS can maximize profits by optimizing fleet size and efficiency, without compromising the benefits of emission reductions. The framework of stakeholder interaction proposed in this study and the results of empirical analysis not only assist regulators, businesses, and the public in better understanding and promoting sustainable production and consumption practices in the sharing economy but also provide valuable insights for achieving a win-win situation of platform profitability and environmental benefits in the SPC practice process. Full article

Next Point-of-Interest (POI) recommendation is aimed at predicting users’ future visits based on their current status and historical check-in records, providing convenience to users and potential profits to businesses. The Graph Neural Network (GNN) has become a common approach for this task due to the capabilities of modeling relations between nodes in a global perspective. However, most existing studies overlook the more prevalent heterogeneous relations in real-world scenarios, and manually constructed graphs may suffer from inaccuracies. To address these limitations, we propose a model called Heterogeneous Graph Structure Learning for Next POI Recommendation (HGSL-POI), which integrates three key components: heterogeneous graph contrastive learning, graph structure learning, and sequence modeling. The model first employs meta-path-based subgraphs and the user–POI interaction graph to obtain initial representations of users and POIs. Based on these representations, it reconstructs the subgraphs through graph structure learning. Finally, based on the embeddings from the reconstructed graphs, sequence modeling incorporating graph neural networks captures users’ sequential preferences to make recommendations. Experimental results on real-world datasets demonstrate the effectiveness of the proposed model. Additional studies confirm its robustness and superior performance across diverse recommendation tasks. Full article