Application of lean, agile, and hybrid supply chain management strategies: evidence from the retail operations of the cruise ship industry

The ‘uncertainty framework’ is one of the best-known theoretical models developed in the domain of the Supply Chain Management (SCM). It claims that aligning SCM strategies with product demand and supply characteristics will lead to significant performance advantage. Existing studies have been largely supportive of the framework; however, the overall verdict is still inconclusive. Furthermore, the scope of those studies is limited predominantly to stable manufacturing organisations, with lack of evidence from other industries, in particular from more complex and dynamic settings. This research, based on the case study design, explores the utility of the uncertainty framework in a complex and dynamic environment of the cruise ship retail operations. The study found that in such conditions matching SCM strategies with product demand and supply characteristics has negligible effect on operational performance. Furthermore, the process of product demand and supply categorisation, product groups alignment with SCM strategies, and performance measurement is more complex than claimed by the authors of the framework. It must be acknowledged, however, that some aspects of the framework are partially supported by this research, namely predicted changes of product characteristics over time, and process of SCM strategies classification. The exploration of the uncertainty framework in complex and dynamic settings of the cruise industry exposed also its main weaknesses, such as oversimplification of the practical reality, and a silent assumption that generic rules can guide selection of SCM strategies in all practical conditions. Moreover, the framework lacks one of the crucial components of a ‘good theory’, namely its limitations. It can be concluded, therefore, that the uncertainty framework in its current form cannot serve as a generic explanatory model applicable in all practical settings.