Resilient marketing in hotel enterprises is a research area that has not been systematically explored. This study is based on the 4Ps theory to conduct a systematic theoretical study of resilient marketing in hotel enterprises and promote the application of resilient marketing in hotel enterprises. Data were collected from Chinese hotel employees (n = 501) through an online survey. Data were analysed using SPSS and AMOS software. confirmatory factor analysis (CFA) combined with structural equation modelling (SEM) was used to explore hotel employees’ perceptions of resilient marketing in hotel companies. The findings suggest that the concept of resilient marketing, constructed through the four dimensions of resilient products, resilient prices, resilient price, and resilient promotions, is better able to help hotel enterprises withstand crises. This study contributes to understanding how Chinese hotel enterprises use the concept of resilient marketing to withstand crises, such as positively adapting to market changes, collaboratively responding to market competition, and resisting and reversing crises situation. It has important theoretical value and practical significance for constructing a theory of resilient marketing for hotel enterprises, promoting the practical development of resilient marketing for hotel enterprises.

The purpose of this study is to explore the relationship among higher vocational college (HVC) students’ social support (SS), learning burnout (LB), and learning motivation (LM), and to further explore the influence regulation mechanism. By analyzing the questionnaire survey data of 500 HVC students, this study found some important conclusions. First, a positive correlation is found between SS and LM, whereas LB exhibits a negative correlation with LM. Second, regression analysis results indicate significant influences of SS and LB on LM, with the latter serving as a partial intermediary between SS and LM. Lastly, analysis of group disparities reveals noteworthy distinctions in SS, LB, and LM across students of varying grades. These discoveries underscore the pivotal roles of SS and LB in molding the LM of HVC students, offering valuable insights for educational practices and policy recommendations. This study benefits the understanding of the key factors in the learning process of HVC students and provides a new direction for further research.

The food insecurity and inadequate management of family farm production is a problem that per-sists today in all corners of the world. Therefore, the purpose of this study was to analyze the socioeconomic and agricultural production management factors associated with food insecurity in rural households in the Machángara river basin in the province Azuay, Ecuador. The information was collected through a survey applied to households that were part of a stratified random sample. Based on this information, the Latin American and Caribbean Household Food Security Measurement Scale (ELCSA) was constructed to estimate food insecurity as a function of socioeconomic factors and agricultural production management, through the application of a Binomial Logit model and an Ordinal Logit model, in the STATA^® 16 program. The results show that head house a married head of household, living in an informal house, having a latrine, producing medicinal or ornamental plants, and the relationship between expenses and income are significant variables that increase the probability of being food insecure. In this way, this research provides timely information to help public policy makers employ effective strategies to benefit rural household that are food vulnerable.

In the context of a globalized economic environment, businesses are facing an increasing number of environmental challenges, prompting them not only to pursue economic benefits but also to focus on environmental protection and social responsibility. Green supply chain management (GSCM) and green innovation have become key strategies for enterprises aiming for sustainable development. This study explores the impact of green supply chain practices on green innovation performance, with a focus on how knowledge management and organizational integration serve as mediating variables in this relationship. Grounded in the resource-based view (RBV) and knowledge-based view (KBV) theories, this research employs surveys and in-depth interviews with companies across various industries, combined with the analysis of structural equation modeling, to reveal the complex relationship between GSCM practices, knowledge management capabilities, levels of organizational integration, and green innovation performance. The results show that GSCM practices significantly enhance corporate green innovation performance through effective knowledge management and organizational integration. These findings enrich the theories of GSCM and green innovation, providing practical guidance for enterprises on how to enhance green innovation performance through strengthening knowledge management and organizational integration. Finally, this study discusses its limitations and suggests possible directions for future research, such as exploring the differences in findings across different industry backgrounds and examining other potential mediating or moderating variables.

Richard’s equation was approximated by finite-difference numerical scheme to model water infiltration profile in variably unsaturated soil^[1]. The published data of Philip’s semi-analytical solution was used to validate the simulated results from the numerical scheme. A discrepancy was found between the simulated and the published semi-analytical results. Morris method as a global sensitivity tool was used as an alternative to local sensitivity analysis to assess the results discrepancy. Morris method with different sampling strategies were tested, of which Manhattan distance method has resulted a better sensitivity measures and also a better scan of input space than Euclidean method. Moreover, Morris method at p = 2 , r = 2 and Manhattan distance sampling strategy, with only 2 extra simulation runs than local sensitivity analysis, was able to produce reliable sensitivity measures (μ^*, σ). The sensitivity analysis results were cross-validated by Sobol’ variance-based method with 150,000 simulation runs. The global sensitivity tool has identified three important parameters, of which spatial discretization size was the sole reason of the discrepancy observed. In addition, a high proportion of total output variance contributed by parameters β and θ_s is suggesting a greater significant digits to reduce its input uncertainty range.

The St. Peter Sandstone of the American Midwest is presented today in textbooks as a simple and unproblematic example of “layer-cake geology.” The thesis of this paper is that the very simplicity of St. Peter Sandstone has made it challenging to characterize. In widely separated states, the sandstone appeared under different names. Several theories about how it formed began to circulate. The story of the St. Peter is not only the story of the assemblage of a stratigraphic unit over a vast area during three centuries, but also the role the study of the provenance of this unit played in the development of sedimentology in the early twentieth century, research that was made all the more challenging by its “simple” mineralogy. Indeed, the St. Peter has been controversial since it was first described.