Embracing methodological evolution and diversity in logistics and supply chain management researchRusso, Ivan; Confente, Ilenia; Holmström, Jan; Öhman, Mikael; Tokar, Travis
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-05-2024-0205
The 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.
Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature reviewWang, Siqi; Cheah, Jun-Hwa; Wong, Chee Yew; Ramayah, T.
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-06-2023-0200
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).Design/methodology/approachBased on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.FindingsLSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.Originality/valueThis study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
Netnography: a research method to study supply chain members' interactions in online communitiesRynarzewska, Ania Izabela; Giunipero, Larry
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-05-2023-0193
The objective of this paper is to further the understanding of netnography as a research method for supply chain academics. Netnography is a method for gathering and gaining insight from industry-specific online communities. We prescribe that viewing netnography through the lens of the supply chain will permit researchers to explore, discover, understand, describe or report concepts or phenomena that have previously been studied via survey research or quantitative modeling.Design/methodology/approachTo introduce netnography to supply chain research, we propose a framework to guide how netnography can be adopted and used. Definitions and directions are provided, highlighting some of the practices within netnographic research.FindingsNetnography provides the researcher with another avenue to pursue answers to research questions, either alone or in conjunction with the dominant methods of survey research and quantitative modeling. It provides another tool in the researchers’ toolbox to engage practitioners in the field.Originality/valueThe development of netnography as a research method is associated with Robert Kozinets. He developed the method to study online communities in consumer behavior. We justify why this method can be applied to supply chain research, how to collect data and provide research examples of its use. This technique has room to grow as a supply chain research method.
Towards a critical realism synthesis of configurational and middle-range theorisingMalik, Mohsin; Ali, Imran
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-05-2023-0185
We present configurational theorising as a novel approach to developing middle-range theory in two steps: (1) we illustrate configurational theorising as a new form of supply chain inquiry by connecting its philosophical assumptions with a methodological execution, and (2) we generate new insights underpinning a middle-range theory for supply chain resilience.Design/methodology/approachWe synthesise information from a range of sources and invoke ‘critical realism” to suggest a five-phase configurational theorising roadmap to develop middle-range theory. We demonstrate this roadmap to explain supply chain resilience by analysing qualitative data from 22 organisations within the Australian food supply chain.FindingsCoopetition and supply chain collaboration are necessary causal conditions, but they need to combine with either supply chain agility or multi-sourcing strategy to build supply chain resilience. Asymmetrical analyses showed that the simultaneous absence of supply chain collaboration, supply chain agility and multi-sourcing results in low supply chain resilience, but coopetition was indifferent to low supply chain resilience. Similarly, high supply chain resilience is possible with the non-presence of supply chain agility and multi-sourcing.Research limitations/implicationsThe configurational middle-range theorising roadmap presented and empirically tested in this paper constitutes a substantial advancement to both theory and the methodological domain.Originality/valueThis is the first attempt at developing a middle-range theory for supply chains by explicitly drawing on configurational theorising.
Bayesian network methodology and machine learning approach: an application on the impact of digital technologies on logistics service qualityMaleki Vishkaei, Behzad; De Giovanni, Pietro
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-05-2023-0195
This paper aims to use Bayesian network (BN) methodology complemented by machine learning (ML) and what-if analysis to investigate the impact of digital technologies (DT) on logistics service quality (LSQ), employing the service quality (SERVQUAL) framework.Design/methodology/approachUsing a sample of 244 Italian firms, this study estimates the probability distributions associated with both DT and SERVQUAL logistics, as well as their interrelationships. Additionally, BN technique enables the application of ML techniques to uncover hidden relationships, as well as a series of what-if analyses to extract more knowledge.FindingsThe results show that the average probability of firms investing in DT for analytics (DTA) is higher than that of investing inDT for immersive experiences (DTIE). Furthermore, adopting both offers only a moderate likelihood of successfully implementing SERVQUAL logistics. Additionally, certain technologies may not directly influence some SERVQUAL dimensions. The application of ML reveals hidden relationships among technologies, enhancing the predictions of SERVQUAL logistics. Finally, what-if analyses provide further insights to guide decision-making processes aimed at enhancing SERVQUAL logistics dimensions through DTA and DTIE.Originality/valueThis research delves into the influence of DTIE and DTA on SERVQUAL logistics, thereby filling a gap in the existing literature in which no study has explored the intricate relationships between these technologies and SERVQUAL dimensions. Methodologically, we pioneer the integration of BN with ML techniques and what-if analysis, thus exploring innovative techniques to be used in logistics and supply-chain studies.
A design science approach to manage spare parts distribution: combining design logic and Goldratt’s thinking processesGupta, Mahesh; Lowalekar, Harshal; Chaudhari, Chandrashekhar V.; Groop, Johan
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-08-2023-0288
Design 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.
Repertory grid technique and Honey’s content analysis: a methodological application to advance qualitative research in OSCMMartins, Ricardo; Siegler, Janaina; Freitas, Jonathan Simões; Santos, Laysse Fernanda Macêdo dos; Barroso, Marina Bastos Carvalhais; Macedo, Roberta de Cássia
2024 International Journal of Physical Distribution & Logistics Management
doi: 10.1108/ijpdlm-01-2023-0054
This paper aims to explain and demonstrate how the Repertory Grid Technique (RGT) and Honey’s Content Analysis (HCA) can make new contributions to the field of Operations and Supply Chain Management (OSCM). The proposition involves integrating these complementary analyses to fortify the rigor of qualitative research and establish robust data analysis protocols to identify the main attributes of interviewees regarding a phenomenon while understanding in their perspective how these attributes impact the desired analysis outcome.Design/methodology/approachThis study uses examples with rich empirical data from 40 interviewees across two organizations. The examples use a protocol that allows the grouping of meanings from different knowledgeable individuals and capturing relevant constructs related to an outcome.FindingsThe combination of RGT and HCA permits researchers to effectively identify and analyze the constructs individuals and groups utilize to comprehend the subject matter under investigation. Consequently, these techniques present a structured means to conduct grounded theory investigations and interpretive research, thereby enabling the iterative development of the preliminary conceptual models necessary for OSCM field advancement.Originality/valueWe present two examples in which the protocol is applied to the field of OSCM. These examples illustrate that the techniques provide valuable opportunities for OSCM research, particularly for addressing the limitations related to sample size. Ultimately, RGT and HCA complement quantitative methodologies by uncovering nuanced variations and micro-foundations within firm- and network-level phenomena, offering insights essential for advancing our understanding of OSCM dynamics in specific contexts.