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PurposeThe purpose of this research is to highlight the significance of advancing research methodologies in logistics, operations and supply chain management. It seeks to expand the scope of research questions and explore areas previously constrained by traditional methodological approaches, thereby enhancing the exploration of complex, real-world business issues.Design/methodology/approachThis commentary introduces and discusses the special issue on “Advances in Research Methodologies for Logistics and Supply Chain Management,” exploring methodological innovations, diversity and their potential to address complex business and disciplinary challenges. The commentary assesses a broad spectrum of methodologies, ranging from traditional qualitative and quantitative approaches to overlooked methods such as qualitative comparative analysis, netnography, design science, Bayesian networks, machine learning and repertory grid technique. This diverse methodological approach enables a comprehensive examination of emerging and ongoing challenges in the supply chain. In the final summary section, we highlight additional areas of research method innovation not covered in this special issue, offering a broader perspective on future directions for methodological advancements in SCM research.FindingsThe findings suggest that integrating less explored methodologies from various disciplines encourages a richer, multi-level analysis of the supply chain management landscape. This integration facilitates a deeper understanding of emerging challenges, such as geopolitical issues, global supply chain disruptions and the integration of new technologies. Additionally, the exploration of ‘white space' in research methodologies indicates significant potential for discovering new insights that bridge practical problems with theoretical contributions.Originality/valueThe value of this methodological diversity extends beyond academic enrichment. It catalyzes the generation of innovative insights crucial for business practitioners, policymakers, consultants and academics. By adopting varied research designs and methodologies, the research note can offer a broader spectrum of analytical perspectives, crucial for uncovering nuanced insights into complex, cross-cultural and relationship-based dynamics in supply chain research.
PurposeThe purpose of this research is to highlight the significance of advancing research methodologies in logistics, operations and supply chain management. It seeks to expand the scope of research questions and explore areas previously constrained by traditional methodological approaches, thereby enhancing the exploration of complex, real-world business issues.Design/methodology/approachThis commentary introduces and discusses the special issue on “Advances in Research Methodologies for Logistics and Supply Chain Management,” exploring methodological innovations, diversity and their potential to address complex business and disciplinary challenges. The commentary assesses a broad spectrum of methodologies, ranging from traditional qualitative and quantitative approaches to overlooked methods such as qualitative comparative analysis, netnography, design science, Bayesian networks, machine learning and repertory grid technique. This diverse methodological approach enables a comprehensive examination of emerging and ongoing challenges in the supply chain. In the final summary section, we highlight additional areas of research method innovation not covered in this special issue, offering a broader perspective on future directions for methodological advancements in SCM research.FindingsThe findings suggest that integrating less explored methodologies from various disciplines encourages a richer, multi-level analysis of the supply chain management landscape. This integration facilitates a deeper understanding of emerging challenges, such as geopolitical issues, global supply chain disruptions and the integration of new technologies. Additionally, the exploration of ‘white space' in research methodologies indicates significant potential for discovering new insights that bridge practical problems with theoretical contributions.Originality/valueThe value of this methodological diversity extends beyond academic enrichment. It catalyzes the generation of innovative insights crucial for business practitioners, policymakers, consultants and academics. By adopting varied research designs and methodologies, the research note can offer a broader spectrum of analytical perspectives, crucial for uncovering nuanced insights into complex, cross-cultural and relationship-based dynamics in supply chain research.
PurposeDesign Science (DS) is a relatively new paradigm for addressing complex real-world problems through the design and evaluation of artifacts. Its constituent methodologies are currently being discussed and established in numerous related research fields, such as information systems and management (Hevner et al., 2004). However, a DS methodology that describes the “how to” is largely lacking, not only in the field of OM but in general. The Theory of Constraints (TOC) and its underlying thinking processes (TP) have produced several novel artifacts for addressing ill-structured real-world operations problems (Dettmer, 1997; Goldratt, 1994), but they have not been analyzed from a DS research standpoint. The purpose of this research is to demonstrate how TOC’s thinking process methodology can be used for conducting exploratory DS research in Operations and Supply Chain Management (OSCM).Design/methodology/approachA case study of spare parts replenishment illustrates the use of TOC’s thinking processes in DS to structure an initially unstructured problem context and to facilitate the design of a novel solution.FindingsTOC’s thinking processes are an effective methodology for problem-solving DS research, enabling the development of novel solutions in initially unstructured and wicked problem situations. Combined with structured CIMO design logic TOC’s thinking process offers a systematic method for exploring wicked problems, designing novel solutions, and demonstrating theoretical contributions.Research limitations/implicationsThe implication for research is that TOC’s thinking process methodology can provide important elements of the lacking “how to” methodology for DS research, not only for the field of OM but in general for the field of management.Practical implicationsThe practical outcome of the research is a novel design for dynamic buffer-based replenishment that extends beyond organizational boundaries.Originality/valueThis work shows how the thinking processes can be used in DS research to develop rigorous design propositions for ill-structured problems.
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