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This study investigates the relevant predictors of customer satisfaction and customer loyalty, and explores the group difference by innovativeness or device type, based on equity theory for emerging devices in the initial market of Korea. The results from an online survey of users of emerging devices and structural equation modeling indicate that utilitarian benefit, hedonic benefit, nonmonetary cost, and alternative attractiveness are significant predictors of customer satisfaction, which in turn affects customer loyalty. Hedonic benefit has a stronger relationship with customer satisfaction for more innovative users and nonmonetary cost has a stronger relationship with customer satisfaction for less innovative users. Nonmonetary cost has a negative relationship with customer satisfaction for netbooks; an additional exploratory analysis produced no such evidence for smartphones. These findings suggest managerial implications for customer loyalty regarding emerging devices.

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Effective customer retention is critical for company survival, especially in a mature mobile telecommunications market. To build on customer retention research, we propose an integrative model capturing the dual relational mechanisms that explain customer resistance to churn. We empirically test the model using data from 815 subscribers who have stayed with their mobile network operators for more than three years. The results show that two contrasting mechanisms, dedication-based and constraint-based relationships, simultaneously determine customer resistance to churn.

This paper evaluates the efficiency of mobile content firms through a hybrid approach combining data envelopment analysis (DEA) to analyze the relative efficiency and performance of firms and principal component analysis (PCA) to analyze data structures. We performed a DEA using the total amount of assets, operating costs, employees, and years in business as inputs, and revenue as output. We calculated fifteen combinations of DEA efficiency in the mobile content firms. We performed a PCA on the results of the fifteen DEA models, dividing the mobile content firms into those having either ‘asset‐oriented’ or ‘manpower and experience‐oriented’ efficiency. Discriminant analysis was used to validate the relationship between the efficiency models and mobile content types. This paper contributes toward the construction of a framework that combines the DEA and PCA approaches in mobile content firms for use in comprehensive measurements. Such a framework has the potential to present major factors of efficiency for sustainable management in mobile content firms and to aid in planning mobile content industry policies.