Value relevance of financial statements in convergence with IFRS: analyses in the abnormal pricing error method

We use an econometrically distinct method to test whether the value relevance of financial statements, especially during convergence with International Financial Reporting Standards (IFRS), has improved in Taiwanese firms in 1990–2011. In contrast to a prior study, our results show that given transformation between two high-quality accounting standards, convergence with IFRS will not lead to further increases in value relevance of financial statements. Our findings may provide implications for international standard-setters and regulators, especially countries undecided about adopting or converging with IFRS.     

Real Earnings Management Uncertainty and Corporate Credit Risk

Abstract

This study examines the accounting information uncertainty effects on corporate credit risk from the perspective of real earnings management (RM) activities by investigating 9565 American bond observations from year 2001 to 2008. The main results show that the volatilities of RM activities significantly and positively affect corporate bond yield spreads when well-known bond spread determinant variables are controlled. In addition, the results are robust to alternative model specifications, including the suspect firm analyses, another less ambiguous measure of abnormal cash flows from operations, and abnormal production cost analyses in manufacturing industry or with control of the input price variation. This research also finds that the positive effects of RM volatilities become weaker if a firm has a lower credit rating. Finally, our results remain hold with considering endogeneity issues and analyst characteristic variables and for another estimation period of RM volatilities.     

The risk in hedge fund strategies: theory and evidence from trend followers

Hedge fund strategies typically generate option-like returns.Linear-factor models using benchmark asset indices have difficultyexplaining them. Following the suggestions in Glosten and Jagannathan(1994), this article shows how to model hedge fund returns byfocusing on the popular 'trend-following' strategy. We use lookbackstraddles to model trend-following strategies, and show thatthey can explain trend-following funds' returns better thanstandard asset indices. Though standard straddles lead to similarempirical results, lookback straddles are theoretically closerto the concept of trend following. Our model should be usefulin the design of performance benchmarks for trend-followingfunds.     

Real Estate and the Arbitrage Pricing Theory: Macrovariables vs. Derived Factors

Two empirical models are used to implement the arbitrage pricing theory: the factor loading model (FLM) and the macrovariable model (MVM). This study compares the ability of these two models to explain real estate returns using equity REIT returns as a proxy. Two tests are performed: a comparison of crosssectional adjusted-R2's and the Davidson and Mackinnon test. The results show that while the two models perform equally well during the period 1974–1979, the MVM outperforms the FLM over the periods 1980–1985 and 1986–1991. In addition, both models suggest superior financial performance for EREITs relative to other investments in the market during the period 1980–1985.     

Maintaining a committed online customer: A study across search-experience-credence products

The goal of relationship marketing is to build and maintain a committed, loyal relationship between a customer and an organization. Although studies have discussed the types of relational bonds that enhance customer loyalty, empirical research that focuses on the application of relational bonds in a virtual environment is relatively sparse. In response, this study investigates the effects of various relational bonds on customer commitment across search-experience-credence goods/services on Internet. The results suggest that financial, social, and structural bonds have positive impacts on customer commitment. In addition, financial bonds are more successful in strengthening customer commitment for search goods/services than for experience or credence goods/services. Structural bonds are more important for credence and experience goods/services than for search goods, and social bonds are almost equally important for all three types of goods/service.     

Tourists' Perception of Authenticity in Indigenous Souvenirs in Taiwan

This study contributes to a body of knowledge concerning tourists' perception of authenticity for indigenous souvenirs in Taiwan. Researchers evaluated, designed, and produced souvenir cups chosen to represent Taiwan's indigenous Paiwan culture. Markers, designs, and materials were researched and selected in order to examine tourists' perceptions of authenticity. Tourists were asked to evaluate the cups and to explain their perceived authenticity and willingness to purchase. The findings suggest that tourists perceive modern design combined with indigenous markers to be more authentic than traditional design. The apparent traditionalism of aboriginal souvenirs does not determine the degree of authenticity. Tourists' perception is specifically grounded in the visuality of the souvenir and their willingness to purchase is also associated with authenticity in design.     

Characteristics of fuzzy synthetic decision methods for measuring student achievement

Traditional method of student achievement evaluation only use arithmetic mean and convert them to rankings, but this does not provide further explanatory information to proceed with more reasonable evaluations, decisions, and interpretations for the learning achievements of students, and provide a fair and appropriate consideration of the evaluation results. Therefore, this study attempts to introduce four types of fuzzy synthetic decision methods in actual scores for evaluating and ranking student’s academic achievement. Using the synthetic decision method of fuzzy theory, the four types of composite operations are used in conjunction with the membership function, and finally fuzzy means are used to express the diverse evaluation results of students. This study uses junior high school first year students in central Taiwan as research subjects, selecting the actual mid-term exam results of the gifted class and general class as research data. The fuzzy synthetic decision method is applied through four types of composite operations, proposing a ranking system that is more diverse and precise than the traditional average method. Finally, this study proposes the characteristics of the four types of fuzzy composite operations, considering the most suitable composite operations for classes with different characteristics. Results of this study can be used as a reference for educators in the field and future researchers. The contribution of this study is to provide the fuzzy grade calculation methods that are suited to students with different characteristics, in order to achieve diverse and precise ranking evaluations.     

Epidemic forecasting with a new fuzzy regression equation

The traditional fuzzy regression model involves two solving processes. First, the extension principle is used to derive the membership function of extrapolated values, and then, attempts are made to include every collected value with a membership degree of at least h in the fuzzy regression interval. However, the membership function of extrapolated values is sometimes highly complex, and it is difficult to determine the h value, i.e., the degree of fit between the input values and the extrapolative fuzzy output values, when the information obtained from the collected data is insufficient. To solve this problem, we proposed a simplified fuzzy regression equation based on Carlsson and Fullér’s possibilistic mean and variance method and used it for modeling the constraints and objective function of a fuzzy regression model without determining the membership function of extrapolative values and the value of h. Finally, we demonstrated the application of our model in forecasting pneumonia mortality. Thus, we verified the effectiveness of the proposed model and confirmed the potential benefits of our approach, in which the forecasting error is very small.     

Personalized mobile advertising: Its key attributes,trends, and social impact

Advertising media are a means of communication that creates different marketing and communication results among consumers. Over the years, newspaper, magazine, TV, and radio have provided a one-way media where information is broadcast and communicated. Due to the widespread application of the Internet, advertising has entered into an interactive communications mode. In the advent of 3G broadband mobile communication systems and smartphone devices, consumers' preferences can be pre-identified and advertising messages can therefore be delivered to consumers in a multimedia format at the right time and at the right place with the right message. In light of this new advertisement possibility, designing personalized mobile advertising to meet consumers' needs becomes an important issue. This research uses the fuzzy Delphi method to identify the key personalized attributes in a personalized mobile advertising message for different products. Results of the study identify six important design attributes for personalized advertisements: price, preference, promotion, interest, brand, and type of mobile device. As personalized mobile advertising becomes more integrated in people's daily activities, its pros and cons and social impact are also discussed. The research result can serve as a guideline for the key parties in mobile marketing industry to facilitate the development of the industry and ensure that advertising resources are properly used.