Search results

In his autobiography, Chen Shui-bian (1999, p. 40) condemned the Koumintang's (KMT's) corruption and praised the Democratic Progressive Party (DPP) for being free from money politics and corruption. The DPP fought the 1992 Legislative Yuan election campaign effectively on an anticorruption platform and used the same strategy in subsequent elections. If Chen Shui-bian had criticized the KMT for its involvement with “black gold” politics and had won the 2000 presidential election on his anticorruption platform, why was he and his family found guilty of corruption after his second term of office? The short answer is that even though he had promised to curb corruption, President Chen himself had succumbed to corruption after assuming office. In June 2002, Keesing's Contemporary Archives cited a poll in Taiwan that indicated that more respondents had perceived the DPP to be more corrupt than the KMT (Copper, 2006, p. 14).

This chapter focuses on pedagogies of working with diversity centers on West-East reciprocal learning through a Reciprocal Learning Program in preservice teacher education between a Canadian university and a Chinese university. By presenting our initial analysis of fieldwork with our Teacher Education Reciprocal Learning Program participants through excerpts from newsletters, surveys, and interviews, we explore how participants from both China and Canada made sense of their learning from the other cultural and educational system through the Reciprocal Learning Program within broad educational, social, and cultural contexts. We argue that both global and multicultural dimensions are cultivated in reciprocal learning that infused the lived experiences of both Canadian and Chinese preservice teacher candidates. We discuss the pedagogic implications for working with diversity and believe that reciprocal learning can take place while working with people from different cultures with an attitude of mutual respect and appreciation and an appetite for learning in our increasingly interconnected world.

This study focuses firstly on the importance for forecasting accuracy of allowing for intervention events in the modeling process. Seasonal autoregressive integrated moving average (SARIMA) models are therefore estimated both with and without intervention effects (the September 11, 2001 events) using data for the period 1990–2001. These models are used to generate forecasts for 2002 and the first part of 2003, and forecast accuracy is assessed using mean absolute percentage error and root mean square percentage error. The second focus of the study is to examine the impacts on tourism demand of the major crises that occurred during the period 2001–2003. The chosen US metropolitan destination is New York City, which was severely affected by the September 11 events, and within New York the US Metropolitan Museum of Art is selected, as this is a very well-known and visited destination for which seasonal data are available over the period 1990–2003. The artificial neural networks (ANNs) and SARIMA forecasts are compared with forecasts generated by the much simpler automatic Holt-Winter's seasonal double exponential smoothing model as well as two naïve forecasting models to ensure that minimum performance standards are being met.

I propose a model of behavior in social interactions where individuals maximize a three-term utility function: a conventional consumption utility term and two “social” terms that capture social preference. One social term is a taste for desert, which is maximized when the individual believes the other person is getting what they deserve. The second social term measures the target individuals’ anger or gratitude from the interaction which is determined by a value function derived from prospect theory. After introducing the model and generating a series of comparative statics results and derived predictions, I report the results of a series of quasi-field experiments on social preferences. I discuss how the model explains several paradoxes of empirical moral philosophy that are less explicable by current economic models of social preference focusing on outcomes and intentions.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

This paper explores the relationship between size, book-to-market, beta, and expected stock returns in the U.S. Information Technology sector over the July 1990–June 2001 period. Two models, the multivariate model and the three-factor model, are employed to test these relationships. The risk-return tests confirm the relationship between size, book-to-market, beta and stock returns in IT stocks is different from that in other non-financial stocks. However, the sub-period results (the periods before and after the technology crash in April 2000) show that the nature of the relationship between stock returns, size, book-to-market, and market factors, or the magnitude of the size, book-to-market, and market premiums, is on average unchanged for both sub-periods. This result suggests the technology stock crash in April 2000 was not a correction of stock prices.