The Profiles of Software Pirates among Tertiary Institutions in Singapore

The study seeks to examine the perception of software piracy as well as to discover its underlying factors among Singapore’s three university communities. Some five hundred responses were gathered from students and staff. By means of cluster analysis and factor analysis, the results identify three clusters of pirate profiles as influenced by factors such as attitudes towards software publishers, general acceptance, convenience, and ethics. The decision tree method links each pirate profile to demographic and computer-related variables. It shows that while age is negatively related to software piracy, computer experience and computer usage demonstrates an ambiguous relationship to software piracy respectively. Further, the undergraduate students tend to be pirates more often than university employees, and the Malays tend to be less frequent pirates as compared to other races. It is hoped that the study will help the relevant policy makers to develop better strategies to protect and to enforce the intellectual property rights among the universities as well as in an increasingly knowledge-based economy such as Singapore.Software Piracy; Software Policy; Protection and Enforcement of Intellectual Property Rights; Cluster Analysis; Factor Analysis.

An Empirical Examination Of Management Control Systems In Just-In-Time Manufacturing

Proponents of JIT techniques often argue that Japanese manufacturing techniques are among the best in the world. On the other hand, critiques have called the JIT manufacturing techniques “management by stress” and that they are often associated with high work intensity, stress, and fatigue. Prompted by some recent findings, organizational theorists began to question whether these new work practices will have a sustaining effect on performance. Consistent with the social technical systems theory, this study suggests that unless complimentary changes also occur in other related systems within an organization, the perceived productivity gain of a new work system may not be realized. Findings provide some support for the hypotheses tested. For example, results show by itself JIT does not lead to performance gains. Similarly, findings show that incentive pay or extrinsic motivation per se is not associated with better manufacturing performance. Instead, results show JIT interacts with performance goals to produce lower manufacturing costs only when incentive pay is used. For plants using fixed pay, however, manufacturing costs are a decreasing function of performance goals but a marginal increasing function of JIT

Profiles, Use, and Perceptions of Singapore Multiple Credit Cardholders

This study analyzes Singapore’s diverse cardholders in search of variations among demographic groups, credit card profiles, and their perceptions with regards to credit card ownership and use, it then discusses possible reasons governing Singaporeans’ credit card ownership and use. A survey was conducted (n = 636), decision trees were then constructed using Chi-square automatic interaction detection algorithm (CHAID) and SPSS software AnswerTree to examine the association between the number of credit cards (target variable) and the demographic characteristics, perceptions and other credit card related variables. The number of credit cards was found to be significantly influenced by income and gender as well as perceptions that include “credit card leads to overspending”, “savings as payment source”, “unreasonable interest rates”, “credit card as status symbol”. The number of credit cards was also affected by credit card related variables such as missing payments sometimes, frequency of use, entertainment expenditures, and petrol purchase. This research provides an in-depth understanding of Singaporean multiple cardholders, thus it is useful in designing marketing strategies for card-issuers as well as anti-debt strategies for policy-makers in Singapore. Despite the importance of consumer credit, virtually no literature or research exists on the ownership and use of credit cards in Singapore, so this paper intends to close this gap. Further, by combining the demographics, cardholders’ profiles and usage patterns with the respondents’ perceptions concerning credit card ownership and use, our study offers a richer analysis to explain consumer behavior than previous literatures.Credit card ownership, credit card use, credit revolving, credit debts, decision tree, Singapore

The determinants of performance in an accountancy degree programme

Earlier research into determinants of academic success in accounting has been conducted primarily in the USA, and has produced inconclusive results. The objective of this study is to investigate the impact of six variables (namely, gender, prior accounting knowledge, academic aptitude, mathematics background, previous working experience and age) on the performance of students in a three-year accountancy degree programme. It is conducted in another educational context, and with control over conditions that may account for the variable results of previous research. The sample comprises 526 students who enrolled in and successfully graduated at the end of a three-year accountancy degree programme in 1990. All the data (i.e., the six variables being investigated and three sets of yearly examination results) have been obtained from official university records. Descriptive statistics, correlation analysis, t-tests, and regression analysis are used to analyse the data. Generally, at the 0.05 significance level, the results show that males and those with previous working experience, and better academic aptitude and mathematics background, as well as younger students performed significantly better in the accountancy degree programme. However, it is found that students with prior (high school) accounting knowledge did not perform as well as students without prior knowledge. Implications of the findings are then discussed.Determinants Of Academic Performance;Performance In Accounting Programmes,

Data mining applications in healthcare.

Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The mass of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these massive data into useful information for decision making. This paper explores data mining applications in healthcare. In particular, it discusses data mining and its healthcare applications in major categories such as the evaluation of treatment effectiveness, management of healthcare, customer relationship management, and detection of fraud and abuse. It also gives an illustrative example of a healthcare data mining application involving the identification of risk factors associated with the onset of diabetes. Finally, the paper highlights the limitations of data mining and discusses some future directions

Study of the demographic and personality characteristics of Simex dealers.

This study draws upon the results of earlier research to identify the key personality characteristics associated with the entrepreneur, namely, high need for achievement, internal locus of control, moderate risk-taking propensity, tolerance for ambiguity, self-confidence and determination and drive

Empirical Investigation of the Factors Affecting Set Results

Investigates the factors affecting student evaluation of teaching (SET). A total of 170 teaching evaluations conducted at the Nanyang Business School (Singapore) were analysed by regressing the overall teaching index on the following variables: subject characteristics (stream, year and type), class characteristics (format, size, time and day), evaluation characteristics (response, time and day), and teacher characteristics (age, gender and rank). Indicates that better teaching evaluation is associated with a smaller class size and a larger number of evaluation responses. Also, teachers of middle‐level subjects receive relatively poorer SET results. Further, SET administered in the later part of the week attract better student evaluation. Finds that teacher characteristics have no significant impact on SET results. Confirms the existence of potential biasing factors, hence, SET should be used with caution and not be the only method of evaluating teachers.</jats:p

Decision Tree Analysis of Terminated Life Insurance Policies

Statistical methods such as regression and survival analysis have traditionally been used to investigate the factors affecting the duration of terminated life insurance policies. This study explores a different approach: it uses a more recently developed data mining technique called decision trees. By sequentially partitioning the data to maximize differences in the dependent variable (duration in this study), the decision trees technique is good at identifying data segments with significant differences in the dependent variable. This identification can be useful when a company is trying to understand the factors driving or associated with the termination of life insurance policies. Decision trees also have an advantage over other techniques such as linear regression in their ability to detect nonlinear and other complex relationships that are more likely to exist in any practical data set