Socio-economic impact of the mHealth adoption in managing diabetes

The increasing prevalence of prediabetes and diabetes has become a serious problem in Korea. This study aims to compare the effects of various policy options for mHealth proliferation for managing and preventing diabetes. To this end, we simulate the plausible possibility of mHealth using system dynamics modelling. There are several important findings of this study that are helpful to policy makers’ decisions. First, innovative healthcare delivery through mHealth has a positive influence on health to significantly reduce prediabetes and diabetes. Moreover, the gap between the healthcare system with and without mHealth increases over time. Second, the effectiveness of mHealth adoption depends on the timing of implementation of institutional reforms. Finally, mHealth adoption can stimulate national economic growth as the demand for a new healthcare system rises.     

Testing linear factor models on individual stocks using the average F-test

In this paper, we propose the average F-statistic for testing linear asset pricing models. The average pricing error, captured in the statistic, is of more interest than the ex post maximum pricing error of the multivariate F-statistic that is associated with extreme long and short positions and excessively sensitive to small perturbations in the estimates of asset means and covariances. The average F-test can be applied to thousands of individual stocks and thus is free from the information loss or the data-snooping biases from grouping. This test is robust to ellipticity, and more importantly, our simulation and bootstrapping results show that the power of the average F-test continues to increase as the number of stocks increases. Empirical tests using individual stocks from 1967 to 2006 demonstrate that the popular four-factor model (i.e. Fama–French three factors and momentum) is rejected in two sub-periods from 1967 to 1971 and from 1982 to 1986.     

The influence of regulations on the efficiency of telecommunications operators: A meta-frontier analysis

The telecommunications industry has a great ripple effect on the overall national economy. However, there is no consensus about what is the optimal regulation policy for the telecommunications industry. Regulations on the telecommunications industry are different by region (i.e. United States, European Union and Asia). A number of studies have been conducted on comparative efficiency analysis for different policies that apply stochastic frontier analysis or data envelope analysis. However, these comparative studies are inappropriate because the production functions for each region are not identical. Thus, this paper addresses meta-frontier methodology, which can reflect differences in production functions. The results indicate that the United States has the highest meta-frontier efficiency in contrast to previous research findings.     

Marketing sustainability: Use of information sources and degrees of voluntary simplicity

The concept of voluntary simplicity (VS) is taken as a starting point to investigate consumers' use of information sources when making purchases of sustainable technological products and services. Differences in information seeking and sources consulted and trusted are investigated with a view to increasing the uptake of sustainable domestic technologies such as energy efficient fridges and washing machines over more grey alternatives. Clear patterns both in sources used and the information seeking process were found between different groups of consumers and priorities for purchase were also identified. The results suggest different strategies for marketing sustainable technologies to these different consumer groups.     

Climate Policy Under Fat-Tailed Risk: An Application of Dice

Uncertainty plays a significant role in evaluating climate policy, and fat-tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question, we propose a new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of the optimal carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman’s Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing the costs of climate change against its benefits, also under deep uncertainty.     

Are we really measuring what we think we're measuring? Assessing attitudes towards destinations with the implicit association test

The study examines individuals' attitudes toward destinations by comparing the results of traditional self‐report surveys with those of the implicit association test (IAT). A total of 84 college students (30 Caucasian, 27 Chinese and 27 Korean) were employed to complete self‐report surveys and computer‐based IATs. The results show that participants' attitudes toward selected destinations (i.e. China and England) vary depending on which of the two different attitude measures is employed. Specifically, it appears that attitudes toward the two countries are not significantly different in self‐report survey, but differences in attitudes are significant in the IAT. This result indicates that greater use of the IAT would enhance our understanding of tourist responses, particularly those related to ability and willingness issues. The implications of the IAT results for tourism destination studies and its relation to explicit measures of attitudes are discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimation of Hybrid Phillips Curve: A Source of Conflicting Empirical Results

Recent empirical studies of the hybrid Phillips curve draw conflicting conclusions about the relative role of forward‐looking behavior and the role of marginal cost as the driving force. It is difficult to identify the source of the conflicting results in past studies because of differences in the measure of inflation, the estimation equation, and the instrumental variables. This article presents evidence that a source of the conflict is the use of suboptimal sets of instruments. When the optimum set of instruments is selected by using the L₂‐boosting method from the principal components of a large number of valid instruments, all conflicting conclusions in previous studies vanish. Regardless of the choice of inflation measure and estimation equation, we identify the dominant role of forward‐looking behavior and a significant effect of the real marginal cost on inflation.