This research examines the relationships between employee creativity and economic development. Data were analyzed with descriptive statistics, tests of reliability and validity, independent t tests, single factor variance analysis, Scheffé posterior comparisons, Pearson product moment correlation analysis, stepwise multiple regression analysis, and so on.
One of the most attractive issues in the construction industry today is cost reduction because depression is coming after Japan's bursting bubbles and spreading to other Asian countries. However, most researchers do not know how to solve this problem because they still know very little about the relationship between cost and output for the construction industry. Therefore, the author tried to analyze the cost function of construction firms with due consideration of their available resources by using Cobb-Douglas Production and Cost Functions in this paper. By statistical analysis, the cost and production functions of Japan's and Taiwan's construction firms were discovered.
An increasing number of colleges and universities are focusing on general issues, thus presenting teachers with new challenges with regard to both pedagogy and expertise. Pertinent literature was reviewed to establish the research basis on which this study rests. Important theories were investigated via questionnaires exploring job stress distributed to academic heads at the 29 technological universities in Taiwan. SPSS, including descriptive statistics, t tests, one-way ANOVA, Tukey's posthoc comparison and Pearson's correlation coefficient were used to analyze the results according to the backgrounds of subjects and their perceptions of job stress.
In this study an interview method was used to investigate the psychological contracts of temporary employees in the Administration Bureau of South Taiwan Science Park. The conclusions offer suggestions about management practices and improvement of the welfare of workers. These suggestions can be used by government agencies that allocate temporary labor and by related departments that hire temporary employees.
Few studies have focused on the different roles risk factors play in the multistate temporal natural course of breast cancer. We proposed a three‐state Markov regression model to predict the risk from free of breast cancer (FBC) to the preclinical screen‐detectable phase (PCDP) and from the PCDP to the clinical phase (CP). We searched the initiators and promoters affecting onset and subsequent progression of breast tumor to build up a three‐state temporal natural history model with state‐dependent genetic and environmental covariates. This risk assessment model was applied to a 1 million Taiwanese women cohort. The proposed model was verified by external validation with another independent data set. We identified three kinds of initiators, including the BRCA gene, seven single nucleotides polymorphism, and breast density. ER, Ki‐67, and HER‐2 were found as promoters. Body mass index and age at first pregnancy both played a role. Among women carrying the BRCA gene, the 10‐year predicted risk for the transition from FBC to CP was 25.83%, 20.31%, and 13.84% for the high‐, intermediate‐, and low‐risk group, respectively. The corresponding figures were 1.55%, 1.22%, and 0.76% among noncarriers. The mean sojourn time of staying at the PCDP ranged from 0.82 years for the highest risk group to 6.21 years for the lowest group. The lack of statistical significance for external validation () revealed the adequacy of our proposed model. The three‐state model with state‐dependent covariates of initiators and promoters was proposed for achieving individually tailored screening and also for personalized clinical surveillance of early breast cancer.
Corruption represents the misuse of public power by government departments for personal gain, hindering a country's economic growth. Corruption cannot be eliminated by implementing the national democratic system, and mature democratic countries also exist with varying degrees of corruption. Corruption affects people's trust in the public sector and the country's economic development. Open government data can help people understand the governance performance of the government to reduce corruption in the public sector. Citizens can use open government data to generate innovative applications and economic value. This study uses a two-stage data envelopment analysis method to assess the anti-corruption efficiency of 21 countries from 2013 to 2017 through open government data, the corruption perception index, and GDP data. Then, the efficiency analyzed is introduced into the BCG (Boston Consulting Group) matrix to observe the distribution of these 21 countries. Analyzing the results showed that Uruguay and Costa Rica in Central and South America are the two most influential countries in fighting corruption. Turkey is at the bottom in the evaluation of anti-corruption efficiency. In addition, discussions of the included countries for their possible improvement in anti-corruption are also provided by using the association rule's analysis. The study results will provide a reference for governments to effectively carry out anti-corruption work in the future.
As coded clinical data are used in a variety of areas (e.g. health services funding, epidemiology, health sciences research), coding errors have the potential to produce far-reaching consequences. In this study the causes and consequences of miscoding were reviewed. In particular, the impact of miscoding due to inadequate medical documentation on hospital funding was examined. Appropriate reimbursement of hospital revenue in the casemix-based (output-based) funding system in the state of Victoria, Australia relies upon accurate, comprehensive, and timely clinical coding. In order to assess the reliability of these data in a Melbourne tertiary hospital, this study aimed to: (a) measure discrepancies in clinical code assignment; (b) identify resultant Diagnosis Related Group (DRG) changes; (c) identify revenue shifts associated with the DRG changes; (d) identify the underlying causes of coding error and DRG change; and (e) recommend strategies to address the aforementioned. An internal audit was conducted on 752 surgical inpatient discharges from the hospital within a six-month period. In a blind audit, each episode was re-coded. Comparisons were made between the original codes and the auditor-assigned codes, and coding errors were grouped and statistically analysed by categories. Changes in DRGs and weighted inlier-equivalent separations (WIES) were compared and analysed, and underlying factors were identified. Approximately 16% of the 752 cases audited reflected a DRG change, equating to a significant revenue increase of nearly AU$575,300. Fifty-six percent of DRG change cases were due to documentation issues. Incorrect selection or coding of the principal diagnosis accounted for a further 13% of the DRG changes, and missing additional diagnosis codes for 29%.The most significant of the factors underlying coding error and DRG change was poor quality of documentation. It was concluded that the auditing process plays a critical role in the identification of causes of coding inaccuracy and, thence, in the improvement of coding accuracy in routine disease and procedure classification and in securing proper financial reimbursement.
A previous study suggests that U.S. Senators trade common stock with a substantial informational advantage compared to ordinary investors and even corporate insiders. We apply precisely the same methods to test for abnormal returns from the common stock investments of Members of the U.S. House of Representatives. We measure abnormal returns for more than 16,000 common stock transactions made by approximately 300 House delegates from 1985 to 2001. Consistent with the study of Senatorial trading activity, we find stocks purchased by Representatives also earn significant positive abnormal returns (albeit considerably smaller returns). A portfolio that mimics the purchases of House Members beats the market by 55 basis points per month (approximately 6% annually).
