2 resultados para Chinese Management

em Duke University


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© 2015 Chinese Nursing Association.Background Although self-management approaches have shown strong evidence of positive outcomes for urinary incontinence prevention and management, few programs have been developed for Korean rural communities. Objectives This pilot study aimed to develop, implement, and evaluate a urinary incontinence self-management program for community-dwelling women aged 55 and older with urinary incontinence in rural South Korea. Methods This study used a one-group pre- post-test design to measure the effects of the intervention using standardized urinary incontinence symptom, knowledge, and attitude measures. Seventeen community-dwelling older women completed weekly 90-min group sessions for 5 weeks. Descriptive statistics and paired t-tests and were used to analyze data. Results The mean of the overall interference on daily life from urine leakage (pre-test: M = 5.76 ± 2.68, post-test: M = 2.29 ± 1.93, t = -4.609, p < 0.001) and the sum of International Consultation on Incontinence Questionnaire scores (pre-test: M = 11.59 ± 3.00, post-test: M = 5.29 ± 3.02, t = -5.881, p < 0.001) indicated significant improvement after the intervention. Improvement was also noted on the mean knowledge (pre-test: M = 19.07 ± 3.34, post-test: M = 23.15 ± 2.60, t = 7.550, p < 0.001) and attitude scores (pre-test: M = 2.64 ± 0.19, post-test: M = 3.08 ± 0.41, t = 5.150, p < 0.001). Weekly assignments were completed 82.4% of the time. Participants showed a high satisfaction level (M = 26.82 ± 1.74, range 22-28) with the group program. Conclusions Implementation of a urinary incontinence self-management program was accompanied by improved outcomes for Korean older women living in rural communities who have scarce resources for urinary incontinence management and treatment. Urinary incontinence self-management education approaches have potential for widespread implementation in nursing practice.

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This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.