Abstract Background Neonatal nurses’ working environments are highly stressful, and burnout is common. This study examines the effect of socioeconomic factors, perceived stress, and social support on neonatal nurse burnout. Methods A total of 311 neonatal nurses participated in this study. They were administered a validated Maslach Burnout Inventory. The study employed a 14-item perceived stress scale (PSS-14) and a social support rate scale (SSRS) to examine stress, socioeconomic factors, and lifestyles. Results Of the neonatal nurses, 40.19% had burnout, 89.60% had mild burnout, and 10.40% had moderate burnout; no neonatal nurse experienced severe burnout. Young nurses and those with low technical skills, poor interpersonal relationships, irregular diet, and insufficient rest were exposed to burnout (all p < 0.05).Most burnout nurses experienced moderate-severe perceived stress, and their PSS-14 scores were higher (all p < 0.05).The scores for objective social support, subjective social support, utilization of social support, total SSRS scores, and the level of social support were all lower in burnout nurses (all p < 0.05). Perceived stress was correlated positively and significantly with emotional exhaustion and personal accomplishment (all p < 0.05). Social support correlated significantly with and reduced personal accomplishments (p < 0.05). Age, poor interpersonal relationships, perceived stress, and social support were all independent factors associated with neonatal nurse burnout (all p < 0.05). Conclusion The prevalence of burnout in neonatal nurses was higher than average. Socioeconomic factors, higher perceived stress, and lower social support contribute to neonatal nurse burnout. Nursing managers should pay attention to socioeconomic factors, perceived stress, and social support among neonatal nurses and employ strategies to reduce neonatal nurse burnout.
Although modern logistics networks (LNs) plays a major role in effectively cutting the cost of enterprise, studies that deal specifically with the dynamics of logistics networks are few, which is very common in circumstance of e-commerce. In order to provide a vehicle for dynamic modeling and analysis of logistics networks operations in vague and uncertain environments, we present our ongoing work on developing a multi-agent model for intra-organizational logistics management and using Lagrangian relaxation to decompose the problem into a set of subproblems.
Abstract While ‘open innovation’ is often considered to be an organisational strategy with universal application, its generalisability and applicability to organisations operating within emerging economies has yet to be fully explored. This study provides empirical evidence of its importance within a substantial sample of Chinese large firms and small and medium enterprises. Using Tobit regression analysis, our findings indicate that external knowledge sources from inter-firm networking are more important in creating the benefits of open innovation for Chinese small and medium enterprises than their larger peers. Linkages to university and research institutes generally have few direct effects on the innovation performance of both large and small firms in China. However, the role of universities and research institutes is shown to be important among our large firm sample when combined with evident internal absorptive capacity. This interaction is generally limited to our large firm sample, and is not as evident among small firms. Our study indicates that the barriers to the adoption of open innovation by Chinese firms might be largely related to the comparatively weak domestic research expertise and limited organisational absorptive capabilities, with this most particularly evident for small and medium enterprises. These findings suggest that, based on this evidence, there is no need for emerging economies like China to mimic the emergence path from closed to open innovation followed by developed countries. Chinese firms will be more likely to garner the benefits available from openness when they develop the capabilities required to identify, assimilate and commercialise knowledge and technologies obtained from external sources.
In recent years, many new logistics organization models (LOMs) emerged at the tactical and operational levels. In order to provide a vehicle for dynamic modeling and analysis of logistics organization operations in vague and uncertain environments, we assess different forms of existing organizations when a store-based sales network coexists with a Web site order network. Three main organizational models can be detected: "store-picking", "dedicated warehouse-picking" and "drop-shipping". We compare the profit and cost of these different models throughout these logistics organizations. The results show that we can adopt an economic logistics organization corresponding to the size of the market.
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