This study aims to configure what dimensions make up for smart phone after service quality, and how this service quality affects customer satisfaction and customer loyalty. Smart phone market is a market of the device leading the digital convergence as well as positioning itself as one of the national growth driving industry. To survive in this matured market, companies should have to respond actively to radical changes and customers needs in the so-called Smart Revolution environment. Lately, however, the smart phone market is prospected to move from growth phase to mature phase by the scholars. In order to proactively respond to the change in such market condition, companies need to provide absolute advantage in customer loyalty over their competitors by revolutionizing the after-sales service quality. Qualified A/S will lead to service satisfaction and achieve customer loyalty. The empirical analysis results obtained through A/S quality are as follows : First, human quality (attitude, expertise, problem-solvability), environment quality (handling agility, convenience, comfort), service policy quality (quality guarantee, additional service operation) are dimensions that make up for A/S quality. Second, A/S quality dimension showed a significant positive influence on service satisfaction and A/S satisfaction showed a positive influence on customer loyalty as well. Based on this empirical study, we propose some implications for A/S quality improvement. First, human quality dimension has relatively higher influence on A/S satisfaction in case of free A/S, so companies need to solve the product problem completely when consumer’s first visit by continual employee education. Second, in case of paid A/S, the service policy quality-especially A/S Warranty period- has higher influence on A/S satisfaction.

Mobile phone market, a market of the device leading the digital convergence as well as positioning itself as one of the national growth driving industry and as a daily necessity, is led globally by companies that have been actively responding to changes in the so-called Smart Revolution environment. Lately, however, the Smart Phone market is prospected to move from growth phase to mature phase by the scholars. In order for a company to proactively respond to the change in such market condition, it is imperative that they ensure absolute advantage in customer loyalty over their competitors by revolutionising the after-sales service(A/S) quality that will lead to service satisfaction. This study aims to configure what dimensions make up for mobile phone A/S quality, and how this quality affects customer satisfaction and loyalty as well as proposing directions for A/S quality improvement by identifying them case by case to see what dimensions have more impact on customer satisfaction.

The development of mobile communication technology is transforming the market of mobile communication devices, which is used to be merely for simple communication, into the one which offers features of personal digital assistant (PDA), fax communica- tion and Internet access. Unlike a mobile phone which comes out as a complete package and whose functions cannot be changed, a smart phone can be upgraded by its user, adding or removing apps as he pleases. OS’s of smart phones are iOS-based Apple, Google Android, Window Mobile, and others. Due to its convenience and powerful features, many people use smart phones its high price. On the other hand, consumer complaints are rising on poor A/S for occasional malfunction. This study analyzes how A/S cases can be classified into groups according to quality factors. We evaluate factors such as consumer impression and consumer satisfaction. By dual quality evaluation using KANO method, we would like to show the different A/S strategy for smart phones, compared with mobile phones.

Researches on after-sales quality have centered on home electric appliances, figuring out how factors influencing after-sales service quality are causally related to customer's behavioral intentions, via consumer satisfaction as an intermediary parameter.