Advances in research methodologies for logistics and supply chain management

Submissions open: 30th September 2022


 Advances in research methodologies are important for the field of logistics and supply chain management (LSCM). These advances not only improve how we as researchers conduct rigorous research, but also also allow us to ask novel and practically relevant questions. These two – advances in methods and advances in the questions we can ask - are connected. Without advances in the available and accepted methods, important problems and questions can remain off-limits for researchers. The present special issue entitled “Advances in research methodologies for logistics and supply chain management” aims to expand the use of new research methodologies and techniques in logistics and supply chain management to improve research, widening the scope of both questions that can be asked, and problems that can be addressed.

New methods for conducting research in the logistics and supply chain management field can result in novel theoretical and/or empirical insights that benefit business practitioners, policy makers, consultants, and academics (Wong, 2021). For example, new analysis methods can provide insights on logistics on a consumer-centric level (Esper et al., 2020), revealing different consumer tactics to optimize order fulfilment options or reduce product returns, and helping retailers and third party logistics reduce the complexity of managing omnichannel retailing (Murfield et al., 2017; Russo et al., 2021).  

All methodological approaches are limited in the type of problems and questions they can address. This also applies to the established LSCM methodologies, and their preferred research methods, both qualitative and quantitative. Thus, as LSCM practice evolves, emerging problems -- such as increasing turbulence and risks in global supply chains; the requirements of circular economy; the opportunities of new technology; meeting changing consumer behaviours -- raise questions that may prompt a need for methodological advances. Recognizing, and addressing emerging problems through methodological advances is one of many reasons that the LSCM field has expanded over the years. As LSCM research expanded its scope of problems, the field has adopted mixed-method approaches from within the discipline, as well as tested novel methodological approaches imported from other disciplines, such as marketing, psychology and sociology, information systems, organizational science and environmental/ ecological science. As a result, we as LSCM researchers are today in a position where we can match new research questions and problems to methodological advances.

Scope of the special issue

In this special issue, we seek original contributions that reflect the recent methodological advances in LSCM research. This comprises new or existing methods and techniques that have potential to address emerging problems, but where applications in LSCM research have previously been limited. Empirical work in LSCM, showcasing methodological advancement, in terms of methods, both qualitative or quantitative, as well as in terms of approaches for insightful framing of emerging research problems, are welcome.

We are particularly interested in papers in LSCM that showcase methodological advances using: 
•    qualitative comparative analysis (QCA); 
•    explorative design science;
•    experiments.  

List of topic areas

To summarize, this SI call encourages LSCM research improving our understanding of the following methodological advances:

  • New Application and Extension adoption of Qualitative comparative analysis (QCA) (interviews, configurational comparison across time, different stakeholders' recipes, data qualitative data calibration)
  • Design as a methodological approach (for problem framing and theoretical contribution; combinatorial innovation; design focused case research)
  • Innovative ways of using technologies, face-to-face interactions, or videography to provide material for experimental research in LSCM.

The call is not limited to these. We are also interested in LSCM papers showcasing methodological advances in:

  • Analysing longitudinal data with secondary data and cases in LSCM research
  • Applicability of qualitative approaches such as behavioural observations (e.g. ethnography) or action research, interventionist research, participatory case study
  • Introduction and/or adaptation of empirical research methodologies from other disciplines to LSCM research.
  • We are also supportive of submissions providing valuable details to help novice researchers avoid methodological pitfalls, including tutorials that presents and discusses methodology as step-by-step processes
  • Purely analytic and mathematic models are not suitable for for this SI in IJPDLM.


Opportunities for Methodological Advances for QCA in LSCM

QCA is a technique that combines qualitative investigation with quantitative analysis through a configural analysis to explain complex situations. Recently, this methodology has also been introduced to the LSCM domain (i.e. Russo et al., 2019, Gligor et al., 2020; Ketchen et al., 2021) with the goal to go beyond exploring the net effects of independent variables on dependent variables.

Internal and external stakeholders in supply chain (e.g. suppliers, manufacturers, logistics service providers, consumers, governments; citizens) often view the same phenomenon (e.g. urban logistics or government norms or green certification standards) differently, and respond using distintly different tactics, requiring a comparative analysis. However, the views of stakeholders, the tactics and the reactions may also change over time. Methodologically, configurational studies in LSCM have underplayed longitudinal dimension and how configurations evolve over time across the dyads and the logistics network. Research exploring and showcasing possible ways of incorporating time into QCA are welcomed, particularly in unstable environments (Misangyi et al., 2017).

Conventionally QCA usually relies on data collected from surveys or secondary data (panel or others). In this special issue we would welcome papers showcasing LSCM papers where QCA employs a qualitative data collected from interviews. In the field of service research Forkmann et al. (2017) has conducted QCA starting with interview results, pointing to an opportunity for methodological advance also in the field of LSCM; this research gap is relevant as the use of qualitative data offers access to deeper observations that support scholars in advancing theory of complex phenomena.

Finally, an opportunity for advancing methodology in LSCM is to use QCA not just for success, but also failure and why specific configurations work and others do not, exploring the solution configurations and corresponding situations that leads to a LSCM choice/strategy to fail (Pappas and Woodside 2021, Ketchen et al (2021).

However, prospective authors must noted that QCA as a method has its limits. It does not lend itself to situations when researchers seek to establish specific causal relationships, such as mediation and moderation (Russo et al. 2019). Potential solutions for such lack could be provided by contributions to this SI.

Opportunities for Methodological Advances for explorative design science in LSCM

From a design science perspective, LSCM is a challenging field. Complex multi-actor environments with potentially diverging incentives (cf. Tanskanen et al. 2015) force us to reflect on core issues of the methodology. First, how is design (as a verb) manifested in this context, and how can we as resaerchers engage in it, or be part of it? Second, how should we study emergent properties and the evolution of designs, and their related outcomes, especially over the long-term? Third, given that design science rests on a pragmatist epistemology, how do we evaluate pragmatic validity in the field of LSCM?

Primed by these questions, we point authors to explorative design science (Holmström et al. 2009). Explorative design science is not a research method (Holmström et al. 2009), but a methodological approach, with the objective to create theoretical insight through developing solutions that solve LSCM problems. By highlighting this distinction, we encourage authors to critically examine and elaborate on their methods in light of explorative design science, rather than copying formalized design science methods from more mature fields (in terms of design science) such as information systems research. By doing so, we believe that LSCM researchers are able to pave the way for methodological advances and new opportunities for exploring technology enabled change in LSCM through design (cf. Gustafsson et al. 2019).

In the special issue we welcome LSCM studies that frame technology enabled change as a design problem, showcasing the use of design logic (cf. Groop et al. 2017) for framing the the research problem, and for specifying the contribution to LSCM literature. We are also interested in papers that showcase the development of an innovative way of operating, through a process of combinatorial innovation, evaluation, and field testing (cf. Öhman et al. 2021 ). Note however that field testing is not a hard requirement, if pragmatic validity can be verified in other ways. Finally, we are interested in papers that in a general sense showcase the design science approach in case studies, especially if they are able to elaborate on the methodological issues pointed out above.

Opportunities for Methodological Advances for experiments in LSCM

In recent years, the issue of methodological rigor has been at the forefront of discussion amongst those conducting experiment-based research in LSCM.  Two prominent examples are the works are Lonati, Quiroga, Zehnder, and Antonakis (2018), and Eckerd, DuHadway, Bendoly, Carter, and Kaufmann (2021).  Out of these discussions has emerged a greater understanding of how to design experiments for both rigor and relevance, as well as a deeper appreciation for important trade-offs one must consider when approaching the design decision.  These contributions alone make these papers must-reads for anyone seeking to conduct experiment-based research and publish in LSCM journals.  However, both of these papers touch on a second methodological issue that has thus far been underappreciated.  Namely, both papers highlight the fact that there are many innovative experiment methodologies that, to date, are rarely seen in LSCM research yet hold tremendous potential for addressing novel and practically relevant research questions.  As part of this special issue, we call for submissions of rigorously designed experiments that make use of underutilized approaches to test theory and inform practice.

Lonati et al. (2018) specifically draw attention to the tremendous opportunity for impactful research available through quasi-experimental designs.  While random assignment of subjects to treatment conditions is generally an essential component a rigorous experiment, there are certain scenarios in which this is not possible yet the research environment offers such potential for insight that an experiment is nonetheless desirable.  An example might include a field setting in which company managers are open to cooperating with researchers on a study, but are unable or unwilling to randomly assign individuals, teams, or facilities to a treatment.   Lonati et al. (2018) discuss three designs for approaching such settings: Difference-in-Differences, Regression Discontinuity, and Synthetic Control Methods.  For this special issue, we invite research based on these (or other) rarely utilized experimental deigns in order to take advantage of unique or insightful research environments.

Further, Eckerd et al. (2021) highlight the opportunity for theory testing that could be unlocked through technological advancements that enhance realism in experiment settings, particularly scenario-based role playing (vignette) experiments.  As settings become more realistic through the creative use of audio and video technology, or even immersive through the use of virtual reality settings, the ecological validity of such studies is greatly enhanced over those using traditional text-based scenarios alone.  This stands to significantly improve the understanding of actual judgment and decision making behaviour of industry managers and consumers.  We invite submissions of experiments utilizing these (or other) technologies to design novel experiments and/or create realistic, engaging scenarios as part of the platform.

Guest Editors: 

Ivan Russo, Department of Business Administration, University of Verona, Italy, [email protected]

Ilenia Confente, Department of Business Administration, University of Verona, [email protected]

Jan Holmström, Department of Industrial Engineering and Management, Aalto University,  [email protected]

Mikael Öhman, Department of Industrial Engineering and Management, Aalto University, [email protected] 

Travis Tokar,  Department of Information Systems and Supply Chain Management, Neeley School of Business, Texan Christian University, [email protected]

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available at here.

Author guidelines must be strictly followed. Please see here.

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”. 

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key deadlines

Opening date: 30th September 2022.
Closing date: 31st May 2023.  


Esper, T. L., Castillo, V. E., Ren, K., Sodero, A., Wan, X., Croxton, K. L., ... & Goldsby, T. J. (2020). Everything Old is New Again: The Age of Consumer‐Centric Supply Chain Management. Journal of Business Logistics, 41(4), 286-293

Forkmann, S., Henneberg, S. C., Witell, L., & Kindström, D. (2017). Driver configurations for successful service infusion. Journal of Service Research, 20(3), 275-291.

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Russo, I., Pellathy, D., & Omar, A. (2021). Managing Outsourced Reverse Supply Chain Operations: Middle‐Range Theory Development. Journal of Supply Chain Management, 57(4), 63-85.

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