Der Logistikdienstleistungssektor ist durch arbeitsteilige sowie kurz-, mittel und langfristige Zusammenarbeit gekennzeichnet. Insbesondere Fourth Party Logistics (4PL) stehen permanent vor der Aufgabe unterschiedliche Logistikdienstleister und damit auch deren Informationssysteme ad-hoc und medienbruchfrei in unternehmensübergreifende Informationsflüsse zu integrieren. Dieser Beitrag stellt verschiedene logistikspezifische Integrationsvarianten, einen modellgetriebenen Integrationsansatz sowie ein Lösungskonzept auf Basis der Logistik Service Engineering & Management (LSEM)-Plattform vor.

Objectives: This Study wanted to analysis the characteristics of the elder adult who had hospitalized with pneumonia. We also evaluated the factors that will affect the unexpected readmission in elderly pneumonia patients. Methods: This is a retrospective cohort study design. The study data was collected 341 pneumonia patients who have hospitalized in a general teaching hospital in Kaohsiung city from year 2009 to 2010. The study population was divided into two groups, the sample size of the old group (age >= 65yrs), and the young group (age < 65yrs) was 173 and 168, respectively. The methods of stepwise multiple logistic regressions were needed to evaluate the association between aging and different days of unplanned readmission in adult pneumonia patients. Results: All the 341 adult pneumonia patients, we found 613 male and 926 female. The demography characteristic of the study subjects, the means of age was 61.9yrs (s.d. = 19.3yrs), and BMI was 23.4 kg/m2 (s.d. = 4.5 kg/m2). The percentage of ICD-9-CM that code 486 was 95.6%. Most patients were community-acquired pneumonia (98.8%), hospitalized from emergency room (85.3%), and admission in general wards (92.7%). The unplanned readmission within 14/30 days, 60 days, and 90days were 9.1%, 11.7%, and 15.0%, respectively. The significant factors that were associated with readmission within 14 days include age, Hb, hospitalized days, hypertension, and other disease. When we used the multiple logistic regression analysis to adjust the other variables, only age still significant with readmission within 14 days (the crude OR of the old group was 4.561, adjusted OR was 2.714, 95% CI of OR from 1.002 to 7.353). In the stepwise multiple logistic regression models, the variable that was associated with readmission with 14 or 30 days were age (>= 65yrs, OR = 3.025), WBC (>=10750 mm3, OR=2.917), and Hb (>=12.4 g/dL, OR=0.390). We remain the elderly subjects to evaluate the factor that will influence readmission states. In all the stepwise logistic regression models, we found the experience with used endotracheal tube in the hospitalized period were the significant increases the readmission rate within 14 or 30 days, 60 days, and 90 days. Conclusion: In our study shows that the situations of unexpected readmission in pneumonia patients were strong association with aging. We suggest that the indicator of medical quality should be adjusted before we comparison the readmission rate in the different institute. The major factors that will be associated to affect the readmission states were endotracheal tube used (significant with 14 or 30 days readmission rate), CRP level (significant with 60 days and 90 days readmission rate), and Hb level (significant with 60 days and 90 days readmission rate).

High quality defense personnel have decisive influence at modern war, and therefore it is the benefit for national security, and the root, garuantee for enhancing military combat power. For years, highly personnel resignation rate has been an important issue for militart personnel resources management. Abnormal resignation rate will not only influences the quality of organizational operation but also disr pts the experience of personnel of the organizational structure.Especially for military services,it will effect our national security and combat power as a whole. General studies of probing resignation were most focuset on factors of resignation will,tendency as probing issues,seldom studies were focused on systematic stuies of resignation rate. Therefore, it is a respond of human resources policies to probe resignation rate in an appropriate way. In this stay, the commissioned and non-commissioned offices in Chinese Marine Corp who stationed in southern Taiwan were taken as probing factors. The predictable capability of Logistic Regression Model has been used in this study as well in order to create the calculation model mode for resignanation rate. The result of the study has been comfirmed that educational level, part-time studies, seniority, marriage, ranking, branch of military services, salary, unit character, welfare and so on were all resignationrelared. Also it is acceptable to predict resignation rate by utilizing this method.

ABSTRACT This research aims at evaluating the risk of home loan, financial institutions generally think that makes enterprises to grant the loan and have a big risk in recent years , turning to and developing consumption financial transaction one after another, the personal home loan has already become the strategic point of every financial institution. The characteristic of the home loan is small for amount of money , there are many pieces , need to spend a large amount of manpower maintaining business operation , so it is fast and clear to verify the way , avoid lacking subjectively and reduce the risk , namely become one of the keys whether this business could be succeeded in promoting. So, the financial institution should set up a set of objective just awarding the way of evaluating the risk, is it verify personnel check and ratify loan amount fast, interest rate and award creed one while being other to help, reach the quantity, the goals of the standardization and automation. This research regards a domestic commercial bank as the main research object, and owe the parent in order to sample of case that is put of all loans now at present with this bank , 2431 normal samples , 381 bad samples of the above three months overdue , total 2812, and award the basic materials of the borrower of forms contained of letter application , and Joint Credit Information Center seek the credit materials that letter in the center inquires is the research range , analyse the background of different borrowers and overdue relation that make loans. Research this real example result can be summed up for as follows. The parameter of risk of showing of the loan is the sex, the age, academic credentials, grace period, family's annual income, round number of the borrowed money, the number of the cash card, interest rate, guarantee debts, whether it is the housing loan of a large number of types, collateral kind

This thesis is based on the stock listing electronic companies in TSE and OTC. There are two purposes of this paper. First, to understand what the difference between failure and non-failure firms under financial factors and corporate governance indicators. And second, to compare with the different material frequency, the predictive ability and the correlation regarding the enterprise crisis reveals the variable whether has a difference. The experiment results show that: By independent-sample t test and logistic regression, we find that under the quarterly financial statements, the profit index is the most manifest factor and the next is debt ratio. The closer to the time of the distress, the more factors in operating efficiency that make the two kinds of the firms differ. Financial distress firms have the higher account receivable turnover rate. In corporate governance factors, the proportion of family members holdings and the rate of directors¡¦ shareholding are the most two important variables. The results from yearly financial reports are similar to which from quarterly financial statements. Profit index and liquidity index can be the prior indications to judge whether a firm gets financial crisis or not. In independent-sample t test, the cash flow from operation ratio and times interest earned are marked variables in the first and second year before bankrupt. The diversity of traditional financial index and the corporate governance variables between failure firms and normal firms are very obvious in the first year previous to failure. In corporate governance factors, the proportion of family members holdings and the extent of the shares as collateral by the board of directors are the most important variables. Regardless of yearly or quarterly financial statements, the closer to the time of the distress, the more different variables appear. The average percentage of correctly classified firms is 80.13% from the 8th to 5th quarter previous to the distress better than 2nd year previous to the distress. Compared with the average accurate prediction rate from the 4th to 1st quarter, the predicting ability from 1st yearly financial statement is better. But the 1st and 2nd accurate rate are 92.54% and 93.44%, the average is 93%. In other words, we can overcome the time lag and raise the predictive ability by using quarterly reports rather than yearly financial statements.

Surface mining and subsequent reclamation often results in the establishment of large areas of grassland that can benefit wildlife. Grasslands have declined substantially over the last 150 years, resulting in declines of many grassland birds. The dickcissel (Spiza americana), a neotropical migrant, is one such bird whose numbers have declined in the last 30 years due to habitat loss, increased nest predation and parasitism, and over harvest (lethally controlled as an agricultural pest on its wintering range in Central and South America). Reclaimed surface-mined lands have been documented to provide important breeding habitat for dickcissels in the United States, emphasizing the importance of reclamation efforts. Objectives were to understand specific aspects of dickcissel nesting ecology (i.e., nest-site selection, nest success, and nest parasitism, and identification of nest predators) on 2 spatial scales on TXU Energy’s Big Brown Mine, near Fairfield, Texas, and to subsequently provide TXU Energy with recommendations to improve reclaimed areas as breeding habitat for dickcissels. I examined the influence of nest-site vegetation characteristics and the effects of field-level spatial factors on dickcissel nesting ecology on 2 sites reclaimed as wildlife habitat. Additionally, I developed a novel technique to identify predators at active nests during the 2003 field season. During 2002–2003, 119 nests were monitored. On smaller spatial scales, dickcissels were likely to select nest-sites with low vegetation, high densities of bunchgrasses and tall forbs, and areas with higher clover content. Probability of nest success increased with nest heights and vegetation heights above the nest, characteristics associated with woody nesting substrates. Woody nesting substrates were selected and bunchgrasses were avoided. Oak (Quercus spp.) saplings remained an important nesting substrate throughout the breeding season. On a larger scale, nest-site selection was likely to occur farther from wooded riparian areas and closer to recently-reclaimed areas. Nest parasitism was likely to occur near roads and wooded riparian areas. Results suggest reclaimed areas could be improved by planting more bunchgrasses, tall forbs (e.g., curly-cup gumweed [Grindelia squarrosa] and sunflower [Helianthus spp.]), clover (Trifolium spp.), and oaks (a preferred nesting substrate associated with higher survival rates). Larger-scale analysis suggests that larger tracts of wildlife areas should be created with wooded riparian areas comprising a minimal portion of a field’s edge.

This thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand the trip underreporting that occurs. The methodology presented here builds on previous research by adding additional variables to the logistic regression model that might be significant in contributing to underreporting, specifically, trip purpose. Understanding the trip purpose is crucial in transportation planning because many of the transportation models used today are based on the number of trips in a given area by the purpose of a trip. The methodology used here was applied to two study areas in Texas, Laredo and Tyler-Longview. In these two study areas, household travel survey data and GPS-based vehicle tracking data was collected over a 24-hour period for 254 households and 388 vehicles. From these 254 households, a total of 2,795 trips were made, averaging 11.0 trips per household. By comparing the trips reported in the household travel survey with those recorded by the GPS unit, trips not reported in the household travel survey were identified. Logistic regression was shown to be effective in determining which household- and trip-related variables significantly contributed to the likelihood of a trip being reported. Although different variables were identified as significant in each of the models tested, one variable was found to be significant in all of them - trip purpose. It was also found that the household residence type and the use of household vehicles for commercial purposes did not significantly affect reporting rates in any of the models tested. The results shown here support the need for modeling trips by trip purpose, but also indicate that, from urban area to urban area, there are different factors contributing to the level of underreporting that occurs. An analysis of additional significant variables in each urban area found combinations that yielded trip reporting rates of 0%. Similar to the results of Zmud and Wolf (2003), trip duration and the number of vehicles available were also found to be significant in a full model encompassing both study areas.

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Due to the global competition, the survival of enterprises must face the major test. Since the poor management of the market will increase number of companies, so the crisis early warning model of business has the necessary to establish. The cause of financial crisis is the main source of financial situation of the deteriorating. Therefore, if we could analysis the facets and weights of potential affect factors through the financial and managerial situation of business to judge the crisis cause of a corporation and establish the early warning model is worth to discuss deeply. The precious year of companies¡¦ data that this study collecting are from the Taiwan Securities Exchange 2006/01/01-2008/12/31 which have been out of the open security market based on the analysis standards and omitting the less information and banking, have total 36 enterprises data for analysis. The application of total variables, this study pre-adapts the TEJ business credit risk indicators to integrate the documentation and analysis the fundamental variables. It can be seen that all the factors have the relationship with each other through this study. This highlights a very important message, and also to the crisis among the factors and normal company with a considerable fluctuations. The judging results of DEA-DA model show that most of the company might be affected with some important factors of interpretation in abnormal situation to let the company in crisis cluster. Through Logistic regression analysis results show that our study forecasting model has the great explanatory power to meet the behavior of interpretation with the crisis and normal companies. By the enterprises crisis model of this study building to assess and forecast the crisis situation have the same results with the simplified model constructing with key factors to affect the original model direction. This study shows a very important fact that the crisis forecasting models will not be simplified to change the outcome which also indicating to increase of variables won¡¦t change the results of the assessment. In accordance with this study proposed model, if value positive that would be show more and more vulnerable to crisis. By other words, if value negative that would be more small vulnerable to crisis.

<p>The future has always caught the attention of the human being. The thirst of exploring the future and to know the unknown has driven the human being toward innovativeness.</p><p>Companies are expanding their operations worldwide since the past few decades. Profit growth coupled with an effective strategy has become the primary need of global companies. Research in this area has given rise to optimization of the supply chain for higher profitability. Considering the overall strategy the company needs to plan production well in advance. The operational planning comes in picture at this moment. In order to reduce excessive inventory at each stage of the production; one should know the demand of the next stage and preferably the end customer demand. The process of sales forecasting is undertaken to predict demand at different stages. It is a complex managerial function and hence needed to be undertaken by a scientific way. The sales forecasting the function includes process of forecasting, administration, hardware, software, users and developers of forecast.</p><p>Historically sales forecasting has been considered as a side activity by most of the companies. Sales forecasting has not been considered as an important function of marketing and finance. Very few companies have seen sales forecasting by a scientific management point of view. Less research has been reported in sales forecasting in comparison to other managerial functions. Planning based on sales forecasting; may be part of a selected strategy for growth and profitability. These facts have attracted us to study sales forecasting as a managerial function.</p><p>The purpose of this study is to describe and analyze the sales forecasting process, sales forecasting system, sales forecasting methods and techniques. Further proposing possibilities of improvements in existing forecasting process is also purpose of this study.</p><p>We have selected three manufacturing companies for this study based on purposive sampling. Considering research interest in phenomenon study; we have selected a qualitative research strategy for this study. We have selected a case study method for our research as it is the most appropriate tool to study the relation between theory and phenomenon. For this research, we have collected the data by semistructured interviews based on a pre formed questionnaire. The questionnaire has been prepared with respect to our research purpose and open ended questions were used to gather extensive data. The data gathered during interviews, have been analyzed by the use of ‘Flow model’ suggested by Miles and Huberman (1994).</p><p>Results from this study shows that there is a need to see ‘sales forecasting’ as a management function rather than a computer activity. To achieve the best information integration throughout the supply chain, increased information visibility is needed. To achieve accuracy in both forecasting and planning; collaborative forecasting may be used. Forecasting software needs to have a suite of methods towards product specific forecasting. The need of customized softwares has also been indicated by this study. The need to measure performance of forecasting by means of accuracy, cost and customer relationship has been concluded.</p>