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Purpose: This paper aims to identify complementary strategies for urban freight logistics in a low emission zone (LEZ) that can be implemented in downtown Medellin, Colombia. The strategies will be executed by identifying the characteristics and problems of the business establishments in the area and the entrepreneurs’ opinions. Design/Methodology/Approach: First, a literature review is performed in order to identify global and complementary strategies for the future LEZ, which is the study subject. Then, a “pilot” zone (a main corridor) of downtown Medellín is selected and the business establishment of the area are identified in order to spot problems and evaluate possible strategies for the future LEZ. This identification and evaluation phase is conducted through an interview with logistics managers in 105 establishments selected in the corridor for analysis. Findings: One of the outstanding findings concerns the specificity of the logistics and mobility problems in downtown Medellin, which is located in Colombia, a developing country. The main problems are traffic congestion, lack of regulation and control in loading and unloading areas, as well as inadequate infrastructure for these operations. These obstacles have a significant impact on business activities and air quality in the area. The proposed solutions to complement the LEZ strategy for freight transport focus on improving regulation, establishing specific loading and unloading areas, exploring sustainable transportation options such as the cargo bike, and supporting small and medium-sized businesses. This emphasizes the complexity of the situation and the need for a comprehensive approach to address these logistical and environmental challenges. Originality/Value: This study focuses on the analysis of urban freight logistics strategies that complement the traffic flow restriction policies imposed by low-emission zones. Unlike other studies that address these two issues independently, this paper specifically examines how to improve a LEZ as a comprehensive strategy to reduce the environmental impact of freight transport. In addition, it is noted that most publications tend to focus on passenger mobility strategies, which highlights the potential for research in the freight logistics field.

Purpose: With this work, we intend to promote research on the application of Operations Management tools in order to assist with decision-making in health crisis situations. During the first six weeks of the COVID-19 crisis in Spain, we have contacted a large number of hospital and health department managers in the Valencian Community and other regions of Spain. The result is that very few, at least when contact was made and at the time of writing this article, had consulted staff members in the Operations Management area for advice on this situation, and they are quite reluctant to do so. This is in spite of the fact that some medical sources also consider this crisis to be one of resources, not merely a medical crisis. Our opinion is that Operations Management can make a useful and valuable contribution to anticipate and improve the management of scarce resources, even in times of crisis. If those responsible for public health or heads of hospitals do not see this usefulness, then there is a huge gap between research and practice in Operations Management and what is transmitted to the healthcare sector. Our aim is to help reduce this gap. Design/methodology/approach: In the first part of the article, we will justify that this crisis, besides being a medical crisis, is also a crisis in terms of resources. We will briefly review some of the Operations Management tools that we believe are appropriate for managing this crisis. We will focus on those that we will illustrate in the second part of the article as a practical example of the action research protocol (only the action planning phase), in which we are currently involved. Findings: Due to the peculiarities of the COVID-19 epidemic, it is reasonable to think that the evolution and duration of each outbreak, and the way it is dealt with, will be different in each hospital and/or each health department. Anticipating the number of patients who will require care and forecasting the consumption of resources over time is complex, due to the long and variable incubation times and the uncontrolled evolution of the treatments needed by each patient. Furthermore, since the evolution of new patient admissions is not homogeneous, the forecasting of requirements is difficult. Providing real-time support and detecting with a certain degree of anticipation the potential levels of demand for health care will enable hospitals to define what stages of the contingency plan to apply and how to (re)assign the available resources in the most efficient way possible. Research limitations/implications: Hardly any current data are available, not only publicly, but also through public health ministries and managers; those that are available are not very reliable and come from studies with non-representative samples. For this reason, all forecasts must be taken with a note of caution, and in particular, designing review mechanisms every time a new set of updated reliable data becomes available (something that occurs on a weekly basis). Originality/value: In this work, we will show an example of a proposal for the practical application of Operations Management tools. Our proposal may be useful to hospital managers and public administrators in the healthcare sector (regional ministries or their equivalents). Each health department, hospital or hospital group will generate the aggregate data that facilitate the calculation of needs as input parameters for the model (available and occupied beds, daily admissions, mean lengths of stay in each healing phase and the percent of patients who evolve from one stage to another in the progression of the disease/healing process) and will be able to analyze how the system responds and evaluate different strategies or mitigating actions. These tools have been shown to be useful and reliable in manufacturing and service contexts that show a strong seasonal demand (both occasional and recurring) requiring a great deal of resources. We believe these situations are analogous to those faced by hospitals and the healthcare system in an epidemic like COVID-19. With them, we could facilitate the aggregate planning of resources for hospital administrators in order to provide them operational support during the COVID-19 contingency plan. However, the array of useful tools for this crisis is not limited to those that we will illustrate. Our intent is to encourage the Operations Management academic community to demonstrate how they contribute to the service of society in this COVID-19 epidemic, providing knowledge that can be extrapolated to other similar situations in the future that we may be unfortunate enough to experience.

This special issue of the Journal of Industrial Engineering and Management is dedicated on the most recent and relevant research, theories and practices in Industrial Engineering and Operations Management presented at the 14th International Conference on Industrial Engineering and Industrial Management and XXIV Congreso de Ingeniería de Organización - CIO 2020. The CIO 2020 was held on 9th and 10th July 2020 in Leganés - Madrid and was organized by the Universidad Politécnica de Madrid (UPM) and Universidad Carlos III de Madrid (UC3M). This conference is promoted by ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización) and AIM (European Academy for Industrial Management).

Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system allows an easier generation of many different alternatives for the supply network configuration.