Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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An Analysis of Perceptual Differences between Shippers and Operators for Service Quality of Frozen and Refrigerated Warehouses

냉동·냉장창고 서비스품질 향상을 위한 화주사 및 운영사의 인식차이 분석에 관한 연구

  • Kim, Gwan-Ha (Graduate School of Logistics, Incheon National University) ;
  • Lee, Hae-Chan (Graduate School of Logistics, Incheon National University) ;
  • Yang, Tae-Hyeon (Graduate School of Logistics, Incheon National University) ;
  • Park, Sung-Hoon (Graduate School of Logistics, Incheon National University) ;
  • Yeo, Gi-Tae (Graduate School of Logistics, Incheon National University)
  • 김관하 (인천대학교 동북아물류대학원) ;
  • 이해찬 (인천대학교 동북아물류대학원) ;
  • 양태현 (인천대학교 동북아물류대학원) ;
  • 박성훈 (인천대학교 동북아물류대학원) ;
  • 여기태 (인천대학교 동북아물류대학원)
  • Received : 2020.01.29
  • Accepted : 2020.04.20
  • Published : 2020.04.28
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Abstract

The factors for service quality improvement of frozen and refrigerated warehouses are derived and the differences in perception about service quality improvement between shippers and operators of frozen and refrigerated cargos are analyzed. The objective of this study is to propose quality improvement measures for frozen and refrigerated cargo services using the importance-performance analysis (IPA). As a result, 15 analysis factors were derived. It was found through independent sample t-test that there is no difference in perception about quality improvement between shippers and operators. Furthermore, four top priority investment areas were derived from the IPA: maintaining temperature and humidity, securing variable storage space, on-time stocking and releasing, and providing information service. Meanwhile, inventory management service ability, on-time stocking and releasing, and reliable cargo storage ability needed urgent improvement. This study has industrial implications in that it proposes practical improvement measures for service quality improvement.

본 연구에서는 냉동·냉장창고의 서비스품질 향상을 위한 요인을 도출하고, 냉동·냉장화물을 취급하는 화주사 및 운영사의 서비스품질 향상에 대한 인식차이를 분석한다. 이를 바탕으로 IPA분석(Importance-Performance Analysis)분석을 활용하여 냉동·냉장화물 서비스품질 향상을 위한 개선방안을 제시하는 것을 목적으로 한다. 연구결과 총 15개 분석요인을 도출하였으며, 독립표본 T-test 결과, 화주사와 운영사 간의 품질향상을 위한 인식에는 차이가 없다는 것을 확인하였다. 또한 IPA분석 결과, 최우선 투자영역에 온·습도유지, 가변적 보관공간 확보, 입·출고 정시성, 정보서비스 제공 등 4개의 요인이 도출되었다. 한편 재고관리 서비스능력, 입출고 정시성, 화물을 안정적으로 보관할 수 있는 능력의 경우 시급한 개선이 필요한 것으로 분석되었다. 본 연구는 서비스 품질향상을 위한 실무적인 개선점을 제시하였다는 점에서 산업적인 시사점을 갖는다.

Keywords

References

  1. Markets and Markets. (2017). Cold Chain Monitoring Market by Component Hardware Sensors and Data Loggers) and Softwar), Application (Pharmaceuticals & Healthcare, Food & Beverages, and Chemicals), Logistics (Storage and Transportation), and Region-Global Forecast to 2023, Markets and Markets. https://www.marketsandmarkets.com/
  2. Korea Maritime Institute. (2017). International Logistics Weekly.
  3. Port of Incheon. (2015). Incheon New Port Refrigeration and Refrigeration Logistics Center Development Project Using LNG Cold Heat.
  4. G. S. Cho & H. G. Kim. (2009). A study on the Improvement of Operation of Refrigerated Warehouses in Busan, Korea International Commercial Review, 24(4), 51-72. https://doi.org/10.18104/kaic.24.4.200912.51
  5. J. H. Lee. (2009). A study on the determinate factors of competitive superiority on the freezing and refrigerating warehouse in Gyeonggi-do, Journal of the Korean Society fo Supply Chain Management, 9(2), 135-145.
  6. T. J. Gu, Y. D. Cha, T. H. Nam & G. T. Yeo. (2017). A Study on the Analysis of Success Factors about Frozen and Refrigerated Warehouses using Fuzzy-AHP, Journal of Digital Convergence, 15(11), 121-131. https://doi.org/10.14400/JDC.2017.15.11.121
  7. I. S. Sun & W. D. Lee. (2012). Analysis of Location Characteristics of Cold and Frozen Storage Warehouse through Logit Models, Journal of korea society for Logistics, 22(5), 190-209.
  8. I. S. Sun & W. D. Lee. (2009). A Study on the Demand Analysis of Cold and Frozen Storage Warehouse by Prediction of Storage Amount, Journal of korea society for Logistics, 19(3), 209-228.
  9. I. S. Sun. (2008). Investigation of Domestic Refrigeration and Freezing warehouses, Journal of Distribution Science, 6(2), 5-19. https://doi.org/10.15722/jds.6.2.200812.5
  10. I. S. Sun. (2012). Analysis of Change of the National Cold and Frozen Storage Warehouse with The Size and Number, Journal of korea society for Logistics, 22(2), 133-154.
  11. D. B. Han, Y. J. Kim, K. I. Yeom, J. R. Shin & Y. S. Baek. (2017). A Study of Simulation on the Refrigerated Warehouse System Based on the Cold Energy of Lng Using the Pro-Ii Simulator. Journal of Hydrogen and New Energy Institute in Korea, 28(4), 401-406.
  12. S. H. Kim. (2017). An Importance-Performance Analysis of Location Selection Factors for International Distribution Center in Port Hinterland, Korea trade review, 42(1), 283-301.
  13. J. H. Yang. (2014). A Study on the Utilization of Parcel Service Quality Factors based using IPA, Korean Journal of Logistics, 22(1), 65-88.
  14. K. H. Park. (2010). The comparison of bicycle user characteristics in Seoul using the IPA analysis, Korean Society of Transporation, 7(3), 109-118.
  15. S. H. Park & S. G. Kim. (2019). Early Childhood Teacher's Perception of Career Education for Young Children: Focusing on IPA, Korea Association for Learner-centered Curriculum and Instruction, 19(11), 159-182.
  16. S. S. Kim. (2018). Difference in Recognition of Internal Customer Service Quality of Outsourcing Staff in Hospital Using IPA, Journal of The Korea Socity of Health Informatics and Statistics), 43(1), 80-88. https://doi.org/10.21032/jhis.2018.43.1.80
  17. K. P. Lee, Y. H. Lee, H. S. Kim & Y. G.Kim. (2019). Study on the Citizen's Perception on the Conservation and Management Utilization Indicators of Hangang Park - Based on IPA Analysis, Korean Society of Environment and Ecology, 1, 100-101.
  18. K. S. Cho, H. K. Kim, H. H. S. (2009). Approach study of refrigerator warehouse operation considering internal layout, The Korean Institute of Industrial Engineers, 5, 123-127.
  19. H. H. Son, L. Rosario & M. M. Rahman. (2010). Numerical simulation of temperature and velocity in a refrigerated warehouse Simulation, International Journal of Refrigeration, 33(5), 1015-1025. https://doi.org/10.1016/j.ijrefrig.2010.02.010
  20. S. M. Pineda & G. Diaz. (2011). Performance of an adiabatic cross-flow liquid-desiccant absorber inside a refrigerated warehouse, International Journal of Refrigeration, 34(1), 138-147. https://doi.org/10.1016/j.ijrefrig.2010.08.005
  21. J. E. Alvwies & D. T. Reindi. (2002). Passive thermal energy storage in refrigerated warehouses, International Journal of Refrigeration, 25(1), 149-157. https://doi.org/10.1016/S0140-7007(00)00080-3
  22. C. N. Liao. & H, P. Kao. (2014). An evaluation approach to logistics service using fuzzy theory, quality function development and goal programming. Computers & Industrial Engineering, 68, 54-64. https://doi.org/10.1016/j.cie.2013.12.001
  23. L. Li, J. B. Ford, X. Zhai & L. Xu. (2012). Relational benefits and manufacturer satisfaction: An empirical study of logistics service in supply chain. International Journal of Production Research, 50(19), 5445-5459. https://doi.org/10.1080/00207543.2011.636388
  24. J. I. Sohn, S. H. Woo & T. W. Kim. (2017). Assessment of logistics service quality using the Kano model in a logistics-triadic relationship. The International Journal of Logistics Management.
  25. J. Dai, W. Che, J. J. Lim & Y. Shou. (2019). Service innovation of cold chain logistics service providers: A multiple-case study in China. Industrial Marketing Management.
  26. R. K. Singh, A. Gunasekaran & P. Kumar. (2018). Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach. Annals of Operations Research, 267(1-2), 531-553. https://doi.org/10.1007/s10479-017-2591-3