This study aims to explore the connotation of “Guanxi” within contemporary Chinese marketing channels and to construct and verify a global management model. The objective is to examine how instrumental and emotional dimensions of Guanxi influence enterprise operations and management processes. A hybrid research methodology combining qualitative and quantitative approaches was employed. In-depth interviews with 30 dealer executives provided qualitative insights, while a large-scale survey with 305 valid responses facilitated quantitative analysis. SPSS22.0 and LISREL8.8 were utilized for data analysis, including reliability, validity, hypothesis testing, and structural equation modeling (SEM). The findings reveal that Guanxi is multi-dimensional, comprising both instrumental and emotional components. Instrumental Guanxi includes factors such as status, prestige, credibility, and decision-making power, while emotional Guanxi encompasses trust, emotional connection, and mutual respect. Both dimensions significantly affect professionalism, shared values, contact frequency, and popularity within marketing channels. Hypothesis testing confirmed the significant relationships between these variables, except for the non-significant impact of popularity on instrumental Guanxi. The mediating effects of flexibility and supervision on the relationship between Guanxi and corporate performance were also significant, highlighting the mechanisms through which Guanxi influences organizational outcomes. Moderating effects of perceived internal incentive fairness and digital collaboration capabilities further amplify these relationships. Finaly, the study underscores the dual importance of strategic utility and emotional resonance in Guanxi, providing a robust model for understanding its impact on business management. These insights are valuable for both researchers and practitioners aiming to leverage Guanxi in enhancing organizational performance and relational strategies.

Objective: to achieve accurately and rapidly the mapping of agricultural land use and crop distribution at the township scale. Methods: this study, based on specific methods, such as, time-series remote sensing index threshold classification and maximum likelihood, classifies each land use type and extracts crop spatial information, under the guidance of Sentinel-2A remote sensing images, to carry out agricultural land use mapping at township scale. And the mapping concerned will be verified by comparing with an agricultural spatial information map of a 0.5 m resolution, which is based on WorldVieW-2 fused images. Results: (1) the area accuracy of grain and oil crop land, vegetable land, agricultural facilities land and garden land is fairly good, with 92.93%, 98.98%, 95.71% and 95.14% respectively, and within 8% variation from actual area; (2) the spatial information of plot boundary, farmland road network, and canal network produced by OSM road data and historical high-resolution images was overlayed with the classification results of Sentinel-2A multi-spectral image for mapping, which can improve the accuracy of plot boundary information of classification results for the image with 10 m resolution. Conclusions: the use of multi-source information fusion method, agricultural land use and crop distribution space big data produced by Sentinel-2A optical image, can effectively improve the accuracy and timeliness of land use mapping at the township scale, to provide technical reference for the application of remote sensing big data to carry out agricultural landscape analysis at the township scale, optimization and adjustment of agricultural structure, etc.

This project analyzes the evolution of the manufacturing sector in Portugal from 2009 to 2021, focusing on the variations in the number of active companies across various subcategories, such as food, textiles, and metal product industries. The goal of this analysis is to understand the dynamics of growth and contraction within each sector, providing insights for companies to adjust their market and operational strategies. Key objectives include analyzing the overall evolution in the number of companies, identifying subcategories with notable changes, and providing a comprehensive analysis of observed trends and patterns. The study is based on data from PORDATA 2024, and the research employs temporal trend analysis, linear and quadratic regression, and the Pareto representation to identify patterns of growth and decline. By comparing annual data, the project uncovers periods of growth and decline, allowing for a deeper understanding of the sector’s dynamics. The findings also highlight variations in periods of economic crises and during the Covid-19 pandemic, and recommendations for action are presented to support businesses resilience and continuity. These results are valuable for companies within the manufacturing sectors analyzed and policy makers, guiding strategic decisions to navigate the complexities of the market dynamics and to ensuring long-term organizational sustainable success.

This study investigated changes in lifestyles and psychological anxiety among Koreans during the Coronavirus Disease 2019 (COVID-19) pandemic using the 2020 data from the nationwide Korean Community Health Survey. The study outcomes were psychological anxiety about the infection and death, due to COVID-19. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the relationship between psychological anxiety and lifestyle changes. During the COVID-19 pandemic, people who practiced healthy behaviors and followed social distancing and quarantine regulations experienced increased psychological anxiety for infection and death. Daily life changes during the COVID-19 pandemic were not associated with psychological anxiety. The result of this study can provide baseline measures for further study on psychological anxiety during re-infection of COVID-19 and future pandemics in Korea.

In this paper, we deal with one of the most urgent and relevant topics nowadays, i.e., water pollution. The problem is finding a valid candidate for the absorption and removal of different kinds of pollutants commonly found in water. There are already some indications about graphene oxide as a potential candidate. In the present work, we take a step forward to show how graphene nanoplatelets (rather than the oxide form of this material) are capable of decontaminating water. In this starting step, we use a specific substance as a model pollutant, i.e., acetonitrile, leaving for the future steps, to extend the analysis to additional types of pollutants. In addition to laboratory-produced graphene nanoplatelets, we already examined in the past; now we wish to consider also commercially available ones, so that the new results will not be bound to a laboratory (low technology readiness level) material, but will become interesting also from the industrial point of view, thanks to the scalability of the nanoplatelets production. For this aim, we compare the performance of two types of filters based on two classes of nanomaterials, i.e., those produced by microwave and ultrasound assisted exfoliation, already analyzed in our earlier works, with those commercially distributed by an Italian company, i.e., NANESA, http://www.nanesa.com/. The latter is an innovative SME involved in the production of graphene-based nanomaterials. We focus here in the graphene nanoplatelets, commercially available in industrial batches (GXNan grades). The present study leads to determine which filtering membrane, among the various types of commercial graphene considered, shows the greatest stability, and the lack of breakage of the membrane, concentrating on such accessory features, given that all types of graphene showed excellent adsorption properties.