Earticle

최근 IT 기업들에서 미래 산업으로 자동차에 관한 관심이 지속적으로 증가 하고 있다. 구글, 애플, 삼성과 같은 IT전문 기업들이 자동차 산업에 뛰어 들어 커넥티드카 무선랜이 장착되어 인터넷 접속이 가능한 자동차 [1] 분야에 많은 연구를 집중 하고 있다. 이러한 시점에서 커넥티드카의 개념에 대해 알아 보고 현재 커넥티드카의 여러 방법 중 하나인 미리링크에 관해 알아 본다. 또한 이러한 커넥티드카의 과도기적인 시점에서 아이폰을 이용한 미러링크의 한 방법을 제안하고 이것을 이용한 커넥티드카의 활용방법에 대해 알아보는 것을 본 연구의 목적으로 한다. 이러한 제안은 현재 자동차를 구매한 많은 사람들이 추가 비용을 들이지 않고 앞으로 출시될 커넥티드카의 기능을 포함 하고 있는 자동차를 미리 경험 할 수 있는 기회가 될 것이며 사용하고 있는 스마트 폰을 통해 자동차를 커넥티드카로 만들 수 있는 경험을 하게 될 것이다.

IT companies are increasingly taking interest in the automobile industry as a major industry of the future. Companies specializing in information technology, such as Google, Apple and Samsung, are actively taking part in the automobile industry and are conducting various research on connected cars. At this point in time, this study aims on understanding the concept of connected cars and the concept of mirror linking, which is one of the many methods in connecting cars. In this transitional period of connected cars, the purpose of this study is to present the method of mirror linking iPhones and to discover how this could be used in connected cars. By turning a normal car into a connected car, simply with a smartphone in hand, the ideas presented in this study will serve as an opportunity for many current automobile owners to experience the functions of connected cars of the future without shouldering additional expenses.

Difficulties of developing strategy for improving impulsive buying (IB), major purchase transaction in supermarkets, had been general case. There is research gap on examining and assessing efficiency of decision variables from supermarkets' point of view, since most IB studies were still focusing on perception and psychological variables of customer's point of view. This article is focusing on fundamental exploration of display, one of supermarket's decision variables, and on development of assessment model to improve IB transaction. IB improvement will enhance supermarket's competitive advantage. Mathematical model is delivered by logistic regression, which then becomes an assessment model. The model was developed by interviewing 110 respondents and observing 55 product group displays in Check-Out Counter (COC) of five supermarkets in Indonesia. The model developed indicates that IB occurred because of the proper arrangement of display profile: space width (SW), product mix complexity inside a group product (COM), and height of level from eye level (LVL). IB responses for the same display profile maybe vary depends on the consumer's queuing time (TM). As managerial implication, this research is suggesting to provide product mix which will expand its space width, to display product closer to eye level, and to maintain proper length of queuing.