BW와 QFD를 활용한 국제물류플랫폼 서비스 품질제고 방안에 관한 연구- 해운물류플랫폼을 중심으로 (Improvement of Service Quality for an International Logistics Platform Using BW and QFD Models- Focused on Shipping Logistics Platforms -)

서지정보

· 발행기관 : 한국무역상무학회
· 수록지 정보 : 무역상무연구 / 101권 / 163 ~ 190페이지
· 저자명 : 송선옥

초록

본 연구는 해운물류플랫폼 이용업체가 기대하는 서비스 품질속성을 실증분석을 통해 규명하고, 이를 서비스 제공업체의 기술적 특성으로 변환시킴으로써 플랫폼 서비스품질 개선시 고려해야 할 실무적 측면의 자료제공을 목적으로 한다. 플랫폼 이용업체가 중요시 하는 품질속성을 규명하기 위해 Kano 및 BW(Better/Worse)분석을 실시한 후 이를 서비스 제공업체 실무진과 인터뷰(브레인스토밍)를 통해 도출된 기술적 특성과 연계시키는 QFD(Quality Function Deployment)분석을 진행함으로써 수요자 측면에서 서비스 품질의 중요성만을 강조한 선행연구와는 달리 공급자 측면에서 어떤 서비스 품질속성에 집중을 해야 하는지 실증분석을 통해 검증한다.

영어초록

This study utilized the BW model and the QFD model to empirically identify the service quality attributes expected by customers of shipping logistics platform participants and transformed these into the technical characteristics of platform service providers, thus offering practical implications for improving platform service quality.
The results of the empirical analysis are as follows: First, based on Kano's quality type classification and Timko's customer satisfaction coefficient, the quality dimensions considered most important by shipping logistics platform users were professionalism (competitive freight rates, customized service proposals and advice, excellence in solving cargo-related problems) and responsiveness (quick feedback to customer requests, offline support). In contrast, the least important quality dimension was convenience (ease of search, simplicity of platform use, easy guidance and learning of usage methods). Although the shipping logistics platform services are in their initial stages, companies familiar with using the platform services have shown a strong demand for professionalism and responsiveness, particularly for two-way communication, rather than the convenience of use.
Second, using the BW model to analyze the quality dimensions with high volatility, where customer satisfaction greatly increases or dissatisfaction significantly rises upon improvement, the results identified information accuracy (accurate shipping information, prompt provision of schedules and change information, timely provision of transport process information), professionalism (competitive freight rates), and responsiveness (quick feedback to customers) as crucial.
Third, the analysis of the QFD model, which translates the requirements of platform service users into technical characteristics from the perspective of service providers, identified that diversification of transportation services, comparison functions for freight rates, complaint and reception processing, linkage functions with other modes of transport, and customized freight offers need priority improvement. In contrast, the provision of market trends and news, statistics data, and analytical materials were ranked lowest for improvement. Moreover, in the process of identifying changes in improvement priorities, quality attributes that rose in rank with applied weights (customer-based task processing, linkage functions with other transportation modes, freight comparison functions, convenient booking) were evaluated as relatively less important but are in fact more crucial quality factors, thus platform service providers should pay attention to these rank changes.
The significance of this study lies in the use of the BW model to classify Kano's quality attributes in more detail, thus accurately identifying the service quality expected by customers and enabling strategic decision-making. It distinguished itself from previous research by calculating the average satisfaction coefficient (ASC) and the average potential index (API) in the process, empirically identifying the important quality attributes that should be prioritized for platform service quality improvement and using these as weights to calculate the relative importance of each quality attribute in QFD model analysis. However, due to the small sample size used in the empirical analysis, there is a limitation in generalizing the study results, necessitating further research with a larger sample size for subsequent studies.

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