Design and development of inventory knowledge discovery system

Inventory management (IM) performance is affected by the forecasting accuracy of both demand and supply. In this paper, an inventory knowledge discovery system (IKDS) is designed and developed to forecast and acquire knowledge among variables for demand forecasting. In IKDS, the TREes PArroting Networks (TREPAN) algorithm is used to extract knowledge from trained networks in the form of decision trees which can be used to understand previously unknown relationships between the input variables so as to improve the forecasting performance for IM. The experimental results show that the forecasting accuracy using TREPAN is superior to traditional methods like moving average and autoregressive integrated moving average. In addition, the knowledge extracted from IKDS is represented in a comprehensible way and can be used to facilitate human decision-making.     

Conflict of interest and the credibility of underwriter analyst recommendations

Brokerage analysts frequently comment on and sometimes recommendcompanies that their firms have recently taken public. We showthat stocks that underwriter analysts recommend perform morepoorly than 'buy' recommendations by unaffiliated brokers priorto, at the time of, and subsequent to the recommendation date.We conclude that the recommendations by underwriter analystsshow significant evidence of bias. We show also that the marketdoes not recognize the full extent of this bias. The resultssuggest a potential conflict of interest inherent in the differentfunctions that investment bankers perform.     

Outcomes and cost analysis of the impact of unit-level nurse staffing on post-discharg utilization

Under a proposal from the Centers for Medicare and Medicaid Services, hospitals would no longer be reimbursed for 30-day re-admissions or emergency department (ED) visits. Increasing RN staffing to reduce post-discharge utilization is one possible solution, but one that is not financially attractive to hospitals. This study demonstrates the impact of fluctuating staffing levels on ED visits within 30 days of discharge. RN overtime and RN vacancies also affected subsequent ED visits. It is important for nurse managers, directors, and administrators to recognize the impact of RN staffing on patient outcomes. Reimbursement models will need to be realigned to benefit both hospitals and payers.