ABSTRACT
This study highlights the major challenges faced by hotel interns in their career development and the human resource management of hotels in the current macroeconomic environment, particularly during the COVID-19 pandemic. The paper developed a conceptual model for organizational identification, turnover intention, and perceived alternative job opportunities in the context of hotel internships. A total of 350 samples were collected from hotel internships in Macau. The presented results indicate that organizational identification has a significant negative impact on turnover intention. In addition, alternative job opportunities do not moderate the relationship between organizational identification and turnover intention. The results also showed that females had a higher level of evaluative identification for hotel internships compared to males. In addition, interns from high-income families had a higher level of evaluative identification compared to those from low- and middle-income families. The theoretical contribution extends the concept of organizational socialization to include internship stages in the field of hospitality management. Finally, this paper proposes measures for managing hotel internships during the COVID-19 pandemic.
ABSTRACT
Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients' suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP;(2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations.
ABSTRACT
Statistics show that 76.74% (4 688) of 6 109 patients with chronic wounds are over 50 years of age; the proportion of patients with underlying diseases in all age groups above 50 years ranges from 78.25% to 100.00%. Among the underlying diseases of chronic wound patients, the top four diseases are diabetes mellitus, cardiovascular and cerebrovascular diseases, hypertension, and respiratory diseases. The above underlying diseases and ages of patients are the susceptibility factors of coronavirus disease 2019 released by National Health Commission of China. It is an unavoidable fact that the patients with chronic wounds have to go to the hospital for treatment prescribed by the physician. At the same time, we found that quite a few patients preferred going far afield in choosing hospital for treatment due to various reasons. During the prevention and control of coronavirus epidemic, this " go far afield" style of seeking medical treatment may increase the exposure risk during travelling. Accordingly, we convened 36 wound care clinics in different regions in Shanghai to implement the " Five Measures" encouraging the patients with chronic wounds to seek medical treatment nearby. The principle of this operation is that when seeking medical treatment, patients with chronic wounds should try their best to reduce the travel distance as much as possible to minimize the exposure risk during the epidemic period, which will in turn support the campaign of epidemic prevention and control.