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This paper aims to apply the heterogeneous autoregressive model of realized volatility (HAR-RV) model to minimum-variance hedge ratio estimation and compares the hedging performance of presenting a model with that of a conventional rolling ordinary-least-square (OLS) hedging model. Moreover, this paper empirically analyzes the relationship between hedging performance and the heterogeneity of investors with different trading frequency in forming the expectation for the spot volatility, futures volatility and the covariance in the market.

Use HAR-RV to form expectations of participants of spots and futures market for the next period volatility based on two parts. One is the current observable realized volatility at the same time scale. The other is the expectation for the next longer time scale horizon volatility. Compare hedging performance with rolling OLS model and HAR-RV model. Present a three-times-scale-length (daily, weekly and monthly) HAR-RV model for the spot and futures returns and volatility to analyze the relationship between the hedging performance and the heterogeneity among participants in each market.

The empirical results show that HAR-RV model outperforms the rolling OLS in terms of variance reduction and expected utility in the out-of-sample period. The results also indicate that the greater variance reduction occurs when investors with different trading frequency have a less heterogeneous expectation for spot volatility and more heterogeneous expectation for futures volatility and the covariance. In addition, the expected utility increases along with lower heterogeneity in spot volatility and higher in futures volatility and the covariance. Hedging performance improves along with decreasing heterogeneity of investors in spot volatility and increasing heterogeneity in futures volatility and the covariance.

This paper considers the heterogeneity of participants in spot and futures market, the authors apply HAR-RV model to MVHR estimation and compare the hedging performance of presenting a model with that of conventional rolling OLS hedging model, providing more evidence in hedging literature. This paper analyzes in depth the relationship between hedging performance and the heterogeneity in the market.

Grounded on the value-based adoption model and innovation diffusion theory, this study examined consumer purchase decisions of mobile Global Positioning System (GPS) navigation apps. In addition, this study also investigated the moderating role that perceived availability of free substitutes (PAFS) plays in the relationship between perceived value and purchase intention. The paper aims to discuss these issues.

Data collected from 219 mobile users were analyzed against the research model using the partial least squares approach.

The results showed that compatibility, relative advantage, perceived enjoyment, perceived cost (positively), and complexity (negatively) influenced these users’ value perceptions and purchase decisions. Furthermore, PAFS significantly weakened the positive relationship between perceived value and purchase intentions.

Based on these findings, the authors provide practical suggestions for mobile app developers to increase mobile app sales. This study also helps advance knowledge of mobile internet marketing.

This study is a pioneering effort in explaining consumer purchase intentions in the context of mobile GPS navigation app.

The purpose of this paper is to investigate the post-adoption stage of Voice over Internet Protocol (VoIP) telephony diffusion, examining usage behavior based on Shih and Venkatesh’s use-diffusion (UD) model.

The research model incorporates technology sophistication, complementary technologies, personal innovativeness, self-efficacy, trust propensity, media exposure, subjective norms, and word-of-mouth (WOM) referrals as UD determinants; rate of use and variety of use as usage variables; intense use, specialized use, nonspecialized use, and limited use as UD patterns; and satisfaction and intention to use future-related technologies as UD outcomes. Data used to test the research model were collected using a web-based online questionnaire form; 360 valid responses were obtained. Partial least squares, multinomial logistic regression, and analysis of variance were used to analyze data.

The results reveal that variety of use, self-efficacy, propensity to trust, media exposure, subjective norms, and WOM referrals increase rate of use, while complementary technologies, personal innovativeness, self-efficacy, media exposure, and subjective norms widen variety of use; variety of use is essential in predicting UD outcomes; when choosing limited use as the reference category, more than half of the UD determinants are capable of predicting UD patterns; and generally, intense users are more satisfied with VoIP telephony, while limited users have less intention to use future-related technologies.

The present study focuses on the post-adoption stage, thereby extending the frontiers of research on the diffusion of VoIP telephony. Academics can obtain some evidence of the explanatory power of the UD model in the context of VoIP telephony use, and practitioners can obtain fresh insights into the dynamics of VoIP telephony usage behavior.