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Most previous studies that examine the controversies involved in transit subsidies concentrate on large metropolitan areas in the United States. The main contribution of this article to the extant literature is that it investigates bus ridership data in small- and medium-sized US cities, which has been primarily ignored in earlier literature. The article also analyzes data on bus commuters, subway commuters, and walkers to workplaces in the eight largest cities with extensive subway systems and 22 other large cities. The analysis employs the 2010 US Census (IPUMS data). Generally, the characteristics of subway commuters are quite different from those of bus commuters. The characteristics of walkers in all the US cities are very similar to those who commute by bus.

The infringements and suits of patents have been increased in many technological fields. Since a patent is an intellectual property to protect inventors' exclusive rights of developed technolog ies, technological pre-occupancy is very important to the devel- opment of companies. For the technological pre-occupancy a patent registration time is surely important. In this paper we propose a predictive model of the patent registration time using survival analysis w ith a Weibull survival regression model and a Cox's propor- tional hazard model. They are modeled on the number of international patent classifications (IPC) codes and keywords. To verify the proposed models, we perform a case study using the retrieved patent documents of 'hybrid vehicle' from the website of United State Patent and Trademark Office (USPTO).

This study proposes the estimators for the mean and its variance of the number of respondents who possessed a rare sensitive attribute based on stratified sampling schemes (stratified sampling and stratified double sampling). This study deals with the extension of the estimation reported in Land et al. [Estimation of a rare sensitive attribute using Poisson distribution, Statistics (2011), in press. DOI: 10.1080/02331888.2010.524300] using a Poisson distribution and an unrelated question randomized response model reported in Greenberg et al. [The unrelated question randomized response model: Theoretical framework, J. Amer. Statist. Assoc. 64 (1969), 520–539]. In the stratified sampling, the estimators are proposed when the parameter of the rare unrelated attribute is known and unknown. The variances of estimators using a proportional and optimum allocation are also suggested. The proposed estimators are evaluated using a relative efficiency comparing variances of the estimators reported in Land et al. dep...

We propose new variants of Land et al.’s [Estimation of a rare sensitive attribute using Poisson distribution. Statistics. 2011. DOI: 10.1080/02331888.2010.524300] randomized response model when a population consists of some clusters and the population is stratified with some clusters in each stratum. The estimator for the mean number of persons who possess a rare sensitive attribute, its variance, and the variance estimator are suggested when the parameter of a rare unrelated attribute is assumed to be known and unknown. The clusters are selected with and without replacement. When they are selected with replacement, the selecting probabilities for each cluster are defined depending on the cluster sizes and with equal probability. In addition, the variance comparison between a probability proportional to size (PPS) and PPS for stratification are performed. When the parameters vary in clusters, the stratified PPS has better efficiency than the PPS.

To examine the asymmetry of financial data in detail, we have considered both the tail dependence with diverse copulas and Jung et al.'s (8) directional dependence by copula. From the empirical study in this paper, we have found that the tail dependence by Patton's (11) modified symmetrized Joe-Clayton copula function did not show the asymmetry property sufficiently because there is no tail dependence for the currency exchange rates of Republic of Korea and Japan against the US dollar after the 2008 financial crisis. However, by using the copula approach for directional dependence, we showed that there exists the asymmetry of the currency exchange rates of Republic of Korea and Japan against the US dollar before and after the 2008 financial crisis because the directional dependence only when existing an asymmetry of data can be found. We conclude that the copula approach for directional dependence can be supplemented to explain the asymmetry property in addition to the tail dependence approach.

PurposeThis study developed a systematic measurement scale for the organizational knowledge creation practices. The authors used five knowledge creation phases – sharing tacit knowledge, creating concepts, justifying concepts, building prototypes, and cross‐leveling knowledge – from Nonaka et al.'s knowledge conversion theory as the theoretical foundation.Design/methodology/approachA total of 914 survey responses collected from 14 for‐profit Korean business organizations representing the country's leading businesses were used to examine the factor structure of those five phases, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).FindingsResults confirmed that the current version of knowledge creation practice measurement, which has five sub‐dimensions along with ten items, is valid and applicable specifically in the Korean for‐profit business context in terms of the psychometric properties of the measurement and measurement factor structure.Research limitations/implicationsThe generalization issue still remains one of the research limitations because all data sets were collected from Korean business organizations. More sample diversity needs to be considered for further research in terms of cross‐cultural comparison research, which could strengthen the validity of the current developed measurement.Practical implicationsFrom the practical standpoint, organizations can utilize this measurement to diagnose their status of knowledge creation, at team and organization levels.Originality/valueThis measurement could promote more dynamic research on areas of knowledge creation in terms of valid and economic size of measurement. From the practical standpoint, organizations can utilize this measurement to diagnose their status of knowledge creation at team and organization levels.

On-board survey is one of the most common survey methods utilized on transit units like buses to obtain vital information regarding customer trip characteristics, travel behavior, demographic characteristics, and customers’ attitude toward services. The quantity and the quality of data collected through on-board surveys are very critical and often are a major concern for transit systems because survey results are used for current or future route planning, modeling, etc. Thus, applying appropriate survey techniques for on-board surveys is crucial to collecting the required amount of data to fulfill the transit system's current and future needs without survey cost and time overruns. This study tested three different on-board survey techniques to quantitatively evaluate the effects of each technique on the overall response rate and unit cost. These three tests are (a) length of questionnaire, (b) incentives, and (c) surveyors. The tests were conducted on selected routes of the Tulsa Transit System. The test results indicate that different combinations of techniques will result in different response rates and unit costs. Thus, good planning and piloting tests for the different on-board survey techniques, and appropriate interpretations of the pilot test results, are crucial to acquiring the expected performance of the main survey while staying within budget.

Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.

The aim of this research is to investigate the moderating role of task-related job autonomy to explain the impact of team creativity on organizational knowledge creation in the school context. From the applied performance improvement standpoint, this research differs from previous studies in that more behavioral constructs were considered rather than policy-related issues in the school context. Hierarchical multiple regression and general linear modeling approaches were utilized to examine the general relations among the constructs and the moderating role of task-related job autonomy. Results show that task-related job autonomy was not found to be a statistically significant moderating construct. This finding is in contrast to that of most previous studies on the workplace performance improvement field due to the internal nature of the school system and environment.

We study a weighted least squares estimator for Aalen's additive risk model with right-censored survival data which allows for a very flexible handling of covariates. We divide the follow-up period into intervals and assume a constant hazard rate in each interval. The model is motivated as a piecewise approximation of a hazard function composed of three parts: arbitrary nonparametric functions for some covariate effects, smoothly varying functions for others, and known (or constant) functions for yet others. The proposed estimator is an extension of the grouped data version of the Huffer and McKeague (1991) estimator. For our model, since the number of parameters is finite (although large), conventional approaches (such as maximum likelihood) are easy to formulate and implement. The approach is illustrated by simulations, and is compared to the previous studies. The method is also applied to the Framingham study data.

PurposeThe purpose of this paper is to develop and validate a measurement tool for assessing organizational knowledge creation practices based on the socialization, externalization, combination, and internalization (SECI) processes of the knowledge creation theory.Design/methodology/approachData were collected from a sample of 455 knowledge workers from four Korean for‐profit organizations, utilizing a systematic procedure, which includes: initial item and domain development based on a comprehensive literature review, reliability assessment and item deduction, and construct validity and psychometric property assessment.FindingsResults show that 17 items related to individual and team members' practices of acquiring and sharing knowledge in organizational contexts measure the four domains of SECI knowledge creation practices.Research limitations/implicationsAlthough samples from Korean business settings indicate a limited generalizability, this study's theory‐grounded item specification and systematic procedure of scale development (i.e. descriptive statistics, reliability and inter‐correlation analysis, exploratory and confirmatory factor analysis using the random split method) can be replicated in future similar studies or scale development research.Originality/valueScores at the individual, group, or firm level can be utilized for comparison or development purposes to promote the collaborative knowledge creation practices in organizations.