The purpose of this study was to explore how consumer traits(technology anxiety and need for interaction) explain attitude toward self-service technologies in fashion retail stores. We examined if technology anxiety influences perceived productivity and attitude toward self-service technologies, and if so, how the need for interaction with employees moderates the impact of technology anxiety on perceived productivity and attitude. For the purpose of the study, a web-based survey with Korean consumers was conducted. The final sample size was 214. Structural Equation Modeling Analysis and PROCESS in SPSS were employed to test the proposed hypotheses. The findings indicated that technology anxiety negatively affected perceived productivity and attitude toward self-service technologies in which perceived productivity affected attitude positively. Need for interaction with employees was found to moderate the relationship between technology anxiety and perceived productivity. It also moderated the relationship between technology anxiety and attitude. This study contributes to the self-service technology literature by identifying two antecedents of consumer attitude toward selfservice technologies: technology anxiety and the need for interaction. The findings further provide valuable insights to retailers and marketers as to how technology anxiety, perceived productivity, and the need for interaction work in enhancing consumer attitude toward self-service technologies in the context of fashion retail.

Service productivity is a brand new concept in the service industry, since it is quite different with conventional productivity. While the productivity in manufacturing is one of the quantitative measures for evaluating process efficiency, the service productivity include the nature of customer satisfaction as well as those of service process efficiency. Customer satisfaction, also called service quality in the service industry is one of the most difficult factors to measure quantitatively due to its intangibility. Hence it is also difficult to measure the service productivity correctly. It is hard to find the existed models for service productivity or related research papers in the literature. In this study, a new model which can be used to measure and evaluate the service productivity considering both the service quality and the productivity of service process is proposed. AHP, one of the well-known multiple-criteria decision-making methods, is applied to deal with both quantitative and qualitative factors in the model. The methodology and the procedures for measuring and evaluating service productivity are also presented.

항만의 서비스 수준은 항만의 운영 및 관리 주체인 터미널운영사(TOC), 항만공사 및 정부의 입장에서 항만간 경쟁력의 기준이 되 며, 항만의 이용 주체인 선사 및 화주의 입장에서는 어느 항만을 선택할 지를 결정하는 중요 지표로도 활용된다. 이러한 지표의 중요성을 고 려하여 컨테이너 부두 및 벌크부두를 대상으로 중요 서비스 지표인 선석 점유율, 선박 대기율, 선석 처리량, 접안 척수, 평균 대기 척수, 평균 대기 시간과 같은 6개 지표를 객관적으로 정의하고 관리할 수 있는 소프트웨어를 개발하였다. 컨테이너 부두는 1개 선석부터 6개 선석까지와 벌크 부두는 1개 선석부터 4개 선석까지를 선택적으로 활용할 수 있도록 6개의 서비스 지표를 산정하여 예측이 가능토록 하였다. 이를 활용 하면 선석점유율 대비 선박 대기율, 선석 처리량, 접안 척수, 평균 대기 척수, 평균 대기 시간을 예측할 수 있다. 추가하여 선박의 도착 패턴에 따라 선박 대기율과 항만의 생산성 지표인 연간 처리량도 어떻게 변화되는지를 예측할 수 있도록 하였다. 결과적으로, TOC 입장에서는 서비 스 지표인 선박 대기율과 생산성 지표인 연간 처리량의 관계에서 최적의 운영 수준을 전략적으로 선택(Trade-off)할 수 있으므로 경쟁 항만 에 대비하여 더 많은 선사 및 화주를 유치할 수 있으므로 터미널 수입도 극대화할 수 있다.