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This paper is based on a panel discussion at EurOMA 2015. The purpose of this paper is to identify a number of barriers to relevant research in humanitarian logistics. The authors propose a charter of ten rules for conducting relevant humanitarian research.

The authors use operations management literature to identify best practices for doing research with practice. The authors compile, condense and interpret opinions expressed by three academics and one practitioner at the panel discussion, and illustrate them through quotes.

The increasing volume of papers published in the humanitarian logistics literature has not led to a proportional impact on practice. The authors identify a number of reasons for this, such as poor problem definition, difficult access to data or lack of contextualization. The authors propose a charter of ten rules that have the potential to make humanitarian logistics research more relevant for practice.

By developing best practices for doing relevant research in humanitarian logistics, this paper enables the academic community and practice to better work together on relevant and impactful research projects. Academic knowledge combined with practice-inspired problems has the potential to generate significant improvements to humanitarian practice.

This paper is the first to address the problem of relevance of humanitarian logistics research. It is also one of the few papers involving a practitioner to discuss practical relevance of research. Through this unique approach, it is hoped that this paper provides a set of particularly helpful recommendations for researchers studying humanitarian logistics.

This paper aims to provide a discussion on the interface and interactions between data, analytical techniques and impactful research in humanitarian health supply chains. New techniques for data capturing, processing and analytics, such as big data, blockchain technology and artificial intelligence, are increasingly put forward as potential “game changers” in the humanitarian field. Yet while they have potential to improve data analytics in the future, larger data sets and quantification per se are no “silver bullet” for complex and wicked problems in humanitarian health settings. Humanitarian health supply chains provide health care and medical aid to the most vulnerable in development and disaster relief settings alike. Unlike commercial supply chains, they often lack resources and long-term collaborations to enable learning from the past and to improve further.

Based on a combination of the authors’ research experience, interactions with practitioners throughout projects and academic literature, the authors consider the interface between data and analytical techniques and highlight some of the challenges inherent to humanitarian health settings. The authors apply a systems approach to represent the multiple factors and interactions between data, analytical techniques and collaboration in impactful research.

Based on this representation, the authors discuss relevant debates and suggest directions for future research to increase the impact of data analytics and collaborations in fostering sustainable solutions.

This study distinguishes itself and contributes by bringing the interface and interactions between data, analytical techniques and impactful research together in a systems approach, emphasizing the interconnectedness.

The purpose of this study is to show that the current complexity of humanitarian operations has only increased the usefulness of system dynamics (SD) in helping decision-makers better understand the challenges they face.

A critical analysis to evaluate how SD methodology has been applied to humanitarian operations.

Today's humanitarian operations are characterized by huge complexity given the increased number of stakeholders, feedback loops, uncertainty, scarce resources and multiple objectives. The authors argue that SD's tools (causal-loop diagram, data layer, simulation model) have the capacity to appropriately capture this complexity, thereby enhancing intuition and understanding.

Researchers and practitioners hesitate to use system dynamics when data is missing. The authors suggest alternatives to deal with this common situation.

The Pan American Health Organization (PAHO) has developed a humanitarian supply management system (SUMA) that records, tracks and reports the flow of donations and purchased goods into a disaster area. While a lot of the received goods are in-kind donations, there is a procurement process triggered by the cash funds to meet specific needs. This procurement process also needs to comply with the humanitarian principles, and is therefore susceptible to manipulations from different stakeholders. SUMA has contributed to all the different deployments with the ability to build transparency and accountability in complex operations. These two contributions help to isolate the political factors from the supply chain and protect the humanitarian principles and space.

This “impact pathways” paper argues that operations and supply chain management (OSCM) could help address the worsening drug shortage problem in high-income countries. This significant societal problem poses difficult challenges to stakeholders given the complex and dynamic nature of drug supply chains. OSCM scholars are well positioned to provide answers, introducing new research directions for OSCM in the process.

To substantiate this, the authors carried out a review of stakeholder reports from six European countries and the academic literature.

There is little academic research and no fundamental agreement among stakeholders about causes of shortages. Stakeholders have suggested many government measures, but little evidence exists on their comparative cost-effectiveness.

The authors discuss three pathways of impactful research on drug shortages to which OSCM could contribute: (1) Developing an evidence-based system view of drug shortages; (2) Studying the comparative cost-effectiveness of key government interventions; (3) Bringing supply chain risk management into the government and economics perspectives and vice versa. Our study provides a baseline for future COVID-19-related research on this topic.

Due to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains.

The authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain.

With increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important.

The performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes.

The authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.

The purpose of this paper is to illustrate the appropriateness of system dynamics (SD) methodology as a tool for humanitarian decision makers to understand the effect of their decisions on humanitarian operations. The authors seek to present the initial stages and preliminary findings of a SD model used to analyze a well‐defined subsystem of humanitarian operations, field vehicle fleet management; then build on this example by identifying an additional area of humanitarian operations for future research using the SD methodology.

Case‐based research was combined with SD methodology to examine the appropriateness of this methodology for use in humanitarian operations.

Humanitarian operations are characterized by multiple actors, feedback loops, time pressures, resource constraints and uncertainty. The authors find that SD has the capacity to accurately represent the dynamic complexity of humanitarian operations, and is therefore an appropriate tool to study these systems.

The well‐defined issue of field vehicle fleet management in humanitarian organizations is used to illustrate an application of SD for humanitarian operations. Due to the difficulty in obtaining necessary data to build the SD model, this study uses estimations based on over three years of research into fleet management in the humanitarian sector. The authors then present an example of a broader but less well‐defined subsystem in the humanitarian sector that can be analyzed using SD methodology to the benefit of the overall humanitarian relief operation.

Decision making in humanitarian operations is usually based on intuition and experience which are not always sufficient to fully understand the global impact of these decisions. SD provides humanitarian decision makers with a method to simulate and compare the impact of alternative decisions that would not be possible in real life situations.

This paper examines the appropriateness of SD methodology to help humanitarians improve the effectiveness of their relief and development programs through better‐informed decision making.

This paper presents one of the first attempts to use SD methodology to build a model for humanitarian operations using a well‐defined subsystem, field vehicle fleet management.

A new era for development is needed and business needs to play a significant role in this era. This paper aims to provide insights into the necessary conditions for such a new era of development and specifically the potential contribution of business and academia.

This explorative study is based on expert interviews and the summary of the discussion of the EABIS Colloquium 2011 (“Corporate Responsibility and Developing Countries”).

Innovative companies are moving from building “shareholder value” to “shared value” for all stakeholders; from “quarterly capitalism” to “long‐term capitalism”. They are also providing resources, open access systems and capital to entrepreneurs and communities to support technology and knowledge transfers. Companies that integrate future development concerns into their business model will be ideally placed to secure long‐term licences to operate, develop loyal new consumer bases, and innovate in new market segments.

The methodology only allows preliminary findings for now. More research (also on the ground) will be needed to identify the necessary strategies business has to adopt to play a potent role in a new era for development.

The paper is based on a rich set of data and combines these findings with the thinking of the EABIS Colloquium 2011. It can be the basis for future research.

Provides a comparison of third‐party logistics services utilization between large manufacturing firms in the USA and Western Europe. All these firms had been utilizing third‐party providers for at least three years, although many had been doing so for five years or longer. The group of Western European firms is more committed to outsourcing, as evidenced by the substantially greater percentage of their total corporate logistics budget allocated to third‐party firms. The strategic decision to utilize third‐party companies is more often made at the corporate level and includes input more frequently from other functional areas in Western European firms. However, many of the findings indicate that the issues faced by both groups of executives are very similar, such as their reservations to outsourcing and their experiences with implementation. Almost all the executives indicated that they are satisfied with the performance of third‐party providers, and would, at least moderately, increase their use of such firms.