DEVELOPMENT OF A MULTI-DIMENSIONAL MATRIX FOR SUPPLY CHAIN MANAGEMENT

Abstract

With the rise of globalisation, more of the world’s cargo depends on sea transportation, spanning countries and continents, increasing the complexity of Supply Chain (SC) operations. Multinational companies and SMEs have faced various challenges adapting to the changing environment. This research explores these complexities and aims to identify the most suitable SC and logistics strategy that companies can incorporate into their business framework. In achieving this, a Multi-Dimensional Matrix (MDM) is developed, firstly by analysing the development of SC and logistics strategies throughout time and dividing them into seven eras. The five earliest eras describe the emergence and development of SCs, while the last two eras (six and seven), establish the literature for the MDM, which is tested for its capability to diagnose and recommend suitable strategies for companies. A conceptual framework for an interactive web-based MDM is designed to illustrate the development of the model and its capability to allow companies to insert their own variables, creating a tailored MDM unique to their company. The MDM incorporates most characteristics of the SC, allocating them into a matrix which has four quarters (Agile, Lean, Leagile and Basic SC). The data collection consists of mixed-methods (quantitative and qualitative) approaches. The qualitative approach is Fuzzy Delphi, where statements are based on the literature, and the experts’ responses are analysed using statistical quantitative methods. The consensus from the Fuzzy Delphi are translated into (If-Then) fuzzy rules, then written as JavaScript and HTML, providing the MDM’s interactive capability. The testing is conducted through semi-structured interviews with a UK-based, global car manufacturer Jaguar Land Rover. The results indicate the usefulness of a diagnostic MDM tool able to recommend a suitable SC and logistics strategies, while allowing companies to choose, tailor and amend options according to their specific requirements; thus allowing companies to analyse and further understand their SC and logistics framework.