National Taipei University of Business

About: National Taipei University of Business is a education organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Spanning tree & Hypercube. The organization has 461 authors who have published 790 publications receiving 11885 citations. The organization is also known as: National Taipei College of Business.

Online word-of-mouth as a predictor of television rating

Abstract: Purpose – Despite the growing importance of online word-of-mouth (WOM) with regard to television (TV) ratings, it is usually excluded from early prediction models. The purpose of this paper is to investigate the role of online WOM in TV ratings predictions, focussing on whether the incorporation of online WOM could improve predictions of TV ratings, and extracts meaningful rules for decision-making. Design/methodology/approach – The author uses online WOM as a potential predictive variable in the TV ratings prediction model. The author matches a list of programs based on TV ratings for the movie channel with internet user reviews and TV ratings information from Yahoo! Movies (YM) and XYZ Company. The data set includes 71 movies, for which the data were analyzed with a hybrid model. Findings – Grey relational analysis shows that online WOM is a useful ex ante determinant of TV ratings. As a predictive variable, it plays an essential role in enhancing TV ratings predictions. The experimental results also in...

The determinants of the transportation outsourcing strategy for the express delivery company

Abstract: This article explores the determinants that affect the transportation outsourcing strategy of the express delivery company in Taiwan. The results show that the following situations result in higher outsourcing probability: customer companies belonging to the high-tech industry, customers bringing higher freight revenue, customers having a better relationship with the case study company, and customers’ company having a bigger scale. The findings provide enterprises with a reference of decision making to follow in implementing the transportation outsourcing measure for different customers’ needs. The outsourcing strategy increases the flexibility of operating funds to enhance customer service quality.

The Generalized Popular Condensation Problem

Abstract: In this paper, we are concerned with the generalized popular condensation problem, which is an extension of the popular matching problem. An instance of the popular matching problem consists of a set of applicants \(A\), a set of posts \(P\), and a set of preference lists. According to the preference lists, the goal is to match each applicant with at most one unique post so that the resulting matching is “popular.” A matching \(M\) mapping from \(A\) to \(P\) is popular if there is no other matching \(M'\) such that more applicants prefer \(M'\) to \(M\) than prefer \(M\) to \(M'\). However, such a matching does not always exist. To fulfill the popular matching requirements, a possible manipulation is to neglect some applicants. Given that each applicant is appended with a cost for neglecting, the generalized popular condensation problem asks for a subset of applicants, with minimum sum of costs, whose deletion results in an instance admitting a popular matching. We prove that this problem is NP-hard, and it is also NP-hard to approximate to within a certain factor, assuming ties are involved in the preference lists. For the special case where the costs of all applicants are equal, we show that the problem can be solved in \(O(\sqrt{n}m)\) time, where \(n\) is the number of applicants and posts, and \(m\) is the total length of the preference lists.

Developing ontology-based EPA for representing accounting principles in a reusable knowledge component

Abstract: This study proposed an ontological EPA model (Event, Principle and Account) for describing accounting principles using a reusable knowledge component. The essential characteristics of the model include: (1) based on traditional accounting definitions for typical accounts (A) and business events (E), where the ontological properties of A and E can be identified. These characteristics can be further used to create a knowledge hierarchy for both A and E; (2) identifies the element P (accounting principle), which in turn can be used to measure the economic effects of events on accounts; (3) creates a relationship between E-P, which identifies how to adopt suitable principles for classifying events; and (4) the inferential (E-P)-A relationship, which identifies the effect of a classified event on resources (or accounts). Following typical knowledge engineering processes, hierarchical knowledge of accounting principles can be represented, stored and reused. EPA examples are demonstrated using OWL-based ontology. This study claims that the knowledge framework developed in EPA can provide a basis for full accounting knowledge creation, storage and sharing.