Job Satisfaction of employees is the most important topic in organization today. There are many scles to measure the degree of employees¡¦ satisfaction. But it also has some problems. To resolve these issues, the study uses item analysis and factor analysis to reconstruct a new job satisfaction scale with 6 subscales and 33 items. Finally the study uses structural equation modeling (SEM) to confirm the new scale. The findings indicate that the six subscales and 33 items job satisfaction scale is a reasonable and an accurate measurement model. The scale includes ¡§Job Achievement¡¨, ¡§Payroll Satisfation¡¨, ¡§Supervision Satisfaction¡¨, ¡§Job Support¡¨, ¡§Coworkers Satisfaction¡¨, and ¡§Promotion Satisfaction¡¨. The study wishes that the reconstruction of Job Satisfaction Scale can be a useful tool in Taiwan.

In this dissertation, we consider a multi-item two-echelon inventory distribution system in which the central warehouse operates with (Q, R) policy, and each local warehouse implements base-stock policy. The objective is to find the policy parameters minimizing the relevant system-wide costs subject to an aggregate mean response time constraint at each facility. We first propose an exact solution procedure based on a branch-and-price algorithm to find the relevant policy parameters of the system considered. Then, we propose four alternative heuristics to find the optimal or near-optimal policy parameters of large practical-size systems. The first heuristic, which we call the Lagrangian heuristic, is based on the simultaneous approach and relies on the integration of a column generation method and a greedy algorithm. The other three heuristics are based on the sequential approach, in which first the order quantities are determined using a batch size heuristic, then the reorder levels at the central warehouse and the basestock levels at the local warehouses are determined through the same method used for the Lagrangian heuristic. We also propose a lower bound for the system-wide cost. Later, we extend our study to compound Poisson demand. The performance of the Lagrangian heuristic is found to be extremely well and improves even further as the number of parts increases. Also the computational requirement of the heuristic is quite tolerable. This makes the heuristic very promising for large practical industry-size problems. The performance of the sequential heuristics is also satisfactory, but not as much as the Lagrangian heuristic.

Facing the global situation and challenges that were getting to be severely competitive, all over the countries in the world started to implement ¡§Government Innovation¡¨ and imported the concept of business operation for promoting the competitive edge. Benchmarking originated in the business industries that had made remarkable success with it. Benchmarking is a process¢wa series of actions, steps, functions, or activities that bring about an end or a result: the identification and importation of best practices to improve performance. This research systematically introduced the contents and application procedure of benchmarking, and probed into the successful experience of implementing benchmarking from advanced countries in the world, then chose Kaohsiung Tzuo-ying District Administration as a case study. After practically applying benchmarking to Kaohsiung Tzuo-ying District Administration and analyzing the results of the questionnaire, there are some findings as follows: 1. The leader¡¦s support and employees¡¦ identification are critical factors for successfully implementing benchmarking. 2. Employees always exclude the implementation of new policy. 3. The work attitude of benchmarking team is very important for the benchmarking project. 4. The benchmarking project needs the support of the benchmarking partner. 5. It¡¦ll be necessary to apply multi-approach to stimulate employee to get involved with benchmarking project. 6. The results of questionnaire indicate that the level of understanding, approval of the benchmarking project and the level of being willing to participate is obviously relevant. According to the above findings, this research offered recommendations for Kaohsiung Tzuo-ying District Administration and Kaohsiung City government as follows: 1. Kaohsiung Tzuo-ying District Administration: . The aspect of enhancing activities of communication and propagation . The aspect of selecting benchmarking team . The aspect of selecting benchmarking item . The aspect of selecting benchmarking partner 2. Kaohsiung City government: . The aspect of incentive measure . The aspect of education and training . The aspect of benchmarking syndicate

With the rapid growth of Internet, more and more information is disseminated in the World Wide Web. It is therefore not an easy task to acquire desired information from the Web environment due to the information overload problem. To overcome this difficulty, two major methods, information retrieval and information filtering, arise. Recommender systems that employ information filtering techniques also emerge when the users¡¦ requirements are too vague in mind to express explicitly as keywords. Collaborative filtering (CF) refers to compare novel information with common interests shared by a group of people for recommendation purpose. But CF has major problem: sparsity. This problem refers to the situation that the coverage of ratings appears very sparse. With few data available, the user similarity employed in CF becomes unstable and thus unreliable in the recommendation process. Recently, several collaborative filtering variations arise to tackle the sparsity problem. One of them refers to the item-based CF as opposed to the traditional user-based CF. This approach focuses on the correlations of items based on users¡¦ co-rating. Another popular variation is the trust-based CF. In such an approach, a second component, trust, is taken into account and employed in the recommendation process. The objective of this research is thus to propose a hybrid approach that takes both advantages into account for better performance. We propose the item-level trust-based collaborative filtering (ITBCF) approach to alleviate the sparsity problem. We observe that ITBCF outperforms TBCF in every situation we consider. It therefore confirms our conjecture that the item-level trusts that consider neighbors can stabilize derived trust values, and thus improve the performance.

Mathematics is an increasingly important aspect of education because of its central role in technology. Learning mathematics at the elementary and middle school levels forms the basis for achievement in high school and college mathematics, and for the broad range of mathematical skills used in the workplace. Especially, the middle school years (e.g., Grade 6-Grade8) are crucial to success in mathematics because students must acquire the skills needed in higher levels of mathematics and complex reasoning ability based on the developmental perspectives on cognition (e.g., Piaget, Vygotsky). The purpose of the current study was to measure and interpret the mathematical achievement growth during the middle school years using some very recent advances (confirmatory multidimensional and longitudinal models) in item response theory. It was found that the relative strength of the content areas (mathematical standards and benchmarks) shifted somewhat across grades in defining mathematical achievement. The largest growth occurred from Grade 6 to Grade 7. The specific pattern of growth varied substantially by the socio-economic status of the student but few differences emerged by gender. The implications of the results for education and for developmental theories of cognitive complexity are discussed.

Cognitive Diagnostic Models (CDMs) are a useful way to identify potential areas of intervention for students who may not have mastered various skills and abilities at the same time as their peers. Traditionally, CDMs have been used on narrowly defined classroom tests, such as those for determining whether students are able to use different algebraic principles correctly. In the current study, the Deterministic Input, Noisy "And" Gate model (DINA; Haertel, 1989; Junker&Sijtsma, 2001) and the Compensatory Reparameterized Unified Model (CRUM; Hartz, 2002), as parameterized by the log-linear cognitive diagnosis model (LCDM; Henson, Templin,&Willse, 2009), were used to analyze the utility of pre-defined cognitive components in estimating students' abilities in a broadly defined, standardized mathematics achievement test. The attribute mastery profile distributions were compared; the majority of students was classified into the extremes of no mastery or complete mastery for both the CRUM and DINA models, though greater variability among attribute mastery classifications was obtained by the CRUM.

This study investigated the efficacy of the lz person fit statistic for detecting aberrant responding with unidimensional pairwise preference (UPP) measures, constructed and scored based on the Zinnes-Griggs (ZG, 1974) IRT model, which has been used for a variety of recent noncognitive testing applications. Because UPP measures are used to collect both "self-" and "other-" reports, I explored the capability of lz to detect two of the most common and potentially detrimental response sets, namely fake good and random responding. The effectiveness of lz was studied using empirical and theoretical critical values for classification, along with test length, test information, the type of statement parameters, and the percentage of items answered aberrantly (20%, 50%, 100%). We found that lz was ineffective in detecting fake good responding, with power approaching zero in the 100% aberrance conditions. However, lz was highly effective in detecting random responding, with power approaching 1.0 in long-test, high information conditions, and there was no diminution in efficacy when using marginal maximum likelihood estimates of statement parameters in place of the true values. Although using empirical critical values for classification provided slightly higher power and more accurate Type I error rates, theoretical critical values, corresponding to a standard normal distribution, provided nearly as good results.

This dissertation study was designed to examine measurement equivalence of the Center for Epidemiological Studies Depression (CES-D) Scale across White, African American, and Mexican American elders. Specific aims were to identify race/ethnicity-, sociodemographic-, and acculturation and instrument language-related measurement bias in the CES-D. Three studies were conducted in this dissertation to accomplish these aims. Two existing national datasets were used: the New Haven Established Populations for Epidemiologic Studies of the Elderly (EPESE) for the White and African American samples and the Hispanic Established Populations for Epidemiologic Studies of the Elderly (H-EPESE) for the Mexican-American sample. Differential item functioning (DIF) analyses were conducted using both confirmatory factor analysis (CFA) and item response theory (IRT) methods. Study 1 focused on the role of race/ethnicity on the measurement bias in the CES-D. Results from Study 1 showed a lack of measurement equivalence of the CES-D among Mexican Americans in the comparison with both Whites and Blacks. Race/ethnicity-specific items were also identified in Study 1: two interpersonal relation items in Blacks and four positive affect items in Mexican Americans. Study 2 focused on identifying sociodemographic-related measurement bias in responses to the CES-D among diverse racial/ethnic groups. Results from Study 2 showed that gender and educational attainment affected item bias in the CES-D. The interaction between gender and educational level and race/ethnicity was also found in Study 2: Mexican American women and lower educated Blacks had a greater predisposition to endorse the 'crying' item. Focusing on Mexican American elders, Study 3 examined how level of acculturation and language influence responses to the CES-D. In Study 3, acculturation and instrument language-biased items were identified in Mexican American elders. Study 3 also suggested that acculturation-bias was entirely explained by whether the CES-D was administered in the English or the Spanish versions. Possible reasons for item bias on the CES-D are discussed in the context of sociocultural differences in each substudy. Findings from this dissertation provide a broader understanding of sociocultural group differences in depressive symptom measures among racially/ethnically diverse older adults and yield research and practice implications for the use of standard screening tools for depression.

One of the cornerstones of the R system for statistical computing is the multitude of packages contributed by numerous package authors. This makes an extremely broad range of statistical techniques and other quantitative methods freely available. So far no empirical study has investigated psychological factors that drive authors to participate in the R project. This article presents a study of R package authors, collecting data on different types of participation (number of packages, participation in mailing lists, participation in conferences), three psychological scales (types of motivation, psychological values, and work design characteristics), as well as various sociodemographic factors. The data are analyzed using item response models and subsequent generalized linear models, showing that the most important determinants for participation are a hybrid form of motivation and the social characteristics of the work design. Other factors are found to have less impact or influence only specific aspects of participation. (authors' abstract)

In this report we give a brief introduction to Item Response Theory models and multilevel models. The general assumptions of two classical Item Response Theory, 1PL and 2PL models are discussed. We follow the discussion by introducing a multilevel level framework for these two Item Response Theory Models. We explain Bock and Aitkin's (1981) work to estimate item parameters for these two models. Finally we illustrate these models with a LSAT exam data and two statistical softwares; R project and Stata. / text