School / Department / UnitSupply Chain and Information Management
Funding Scheme/SourceInternational Transport Information Systems Ltd. (ITIS) and Research Matching Grant Scheme (RMGS)
Project TitleDevelopment of Function Deployment Model on Customer, Technological, Core Competency and Supply Chain Risk Analysis for Sustainable Freight Operations Systems
Project Team (HSUHK Staff)Dr Eugene WONG (PI)
Dr Stephen NG (Co-I)
Dr Kev LING (Co-I)
Dr WONG Yiu Man (Co-I)
Dr Helen MA (Co-I)
Dr Kaylee KONG (Co-I)
Project Period2020-11-01 to 2024-12-31 (On-going)
Funding Amount$4,723,200 (in-kind) and $4,723,200 (RMGS)
Other Collaborating PartiesThe Hong Kong Polytechnic University
AbstractSustainable logistics and transport development require the need of continuous enhancement on decision support and enterprise resource planning systems to facilitate more effective operations, stay competitive and resilient in the dynamic environment in the supply chain. This project aims to develop a novel sustainable function deployment (SFD) model based on the model of Zhang and Awasthi (2014), conduct a gap analysis through comprehensive surveys and interviews, and generates priority and recommendation of customer requirements from three perspectives, namely freight and logistics service providers, technology and e-commerce, and competence development. Subject matter experts (SME) from freight forwarders and logistics service providers will be invited for a survey to provide comments on the latest industry trend and coming demands on technology and systems capabilities. SME on technology and ecommerce industry practitioners are also invited to conduct a trial experience run in the system for a designed duration of time and comment on the needs of systems to support the growth in the e-commerce, blockchain, and AI for daily operations in air, maritime and multimodal transport.

The novel SFD to be developed in this project is based on the Zhang and Awasthi (2014) and further designed with reference to the shipping and transport needs, with modification of general requirements to freight forwarder and logistics service provider requirements (F-REQ), technology and e-commerce requirements (T-REQ), and competence development requirements (C-REQ). These requirements will be obtained through the surveys and correlated against the technical requirements, followed by customer requirement prioritisation in order to perform a gap analysis. The methodology, insights and results will be a useful and structured approach for decision makers to select the appropriate areas of improvement in complex freight forwarding operations systems, e.g. ocean freight operation system, air freight operation and management system, financial accounting operation and management system, transportation management system, and regulated air cargo screening facility system. Industry experts and system learners, including newcomers of companies and students, are invited at each phase in participating the survey, with reference to the adoption of ERP-based transport system in achieving the learning outcomes.

With the severe impact on COVID-19 outbreak, supply chains are broken due to factory closure, partial stoppage in terminal, blank sailings of vessels, new custom measures, and safety rules on truck drivers. Daily necessities are of vital importance for retailers and logistics service providers to maintain the delivery to the consumers. Are the current transport systems capable to alert and predict the delivery supply chain and transport risk involved and perform recovery actions in a faster way to ensure a smooth cargo fulfilment and a resilience supply chain? A risk assessment analysis with reference to the ERP-based transport systems will be carried out, upon the review of literature studies, e.g. risk assessment matrix prioritisation and probability calculation, factor analysis and evaluation and quantitative risk assessment (QRA).

Selected Publications

Wong, E. Y. C., Ling, K. K. T., & Zhang, X. (2021). Yield and port performance shipping allocation model forrevamp service deployments under a dynamic trading landscape. Transportation Research Part C: EmergingTechnologies, 130, 103279.