Search

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).

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.

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.

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.