PurposeThe aim of this study is to analyze Turkey's blood collection efficiency at the regional level between 2018 and 2021 and discuss managerial implications.Design/methodology/approachThe authors utilize data envelopment analysis (DEA) to evaluate the efficiency scores of the 18 regions for which the Turkish Red Crescent is responsible. The data set is obtained from the General Directorate of Blood Services in the Turkish Red Crescent.FindingsThe results reveal that the efficient regions over the years did not substantially change, and regions that were consistently efficient for a four-year period are identified. Another finding is that COVID-19 did not affect the blood collection efficiency of the regions. Moreover, the findings illustrate that concentrating on the operations would contribute more to the blood collection efficiency than changing the scale size. Furthermore, the authors observe that the service population is by far the most important variable in determining the efficiency of the regions.Originality/valueIn this study, the authors present a multi-dimensional perspective on the performance evaluation of blood collection operations. In addition, the authors present blood bank managers' feedback on the performance evaluation model, outlining managerial implications. Furthermore, the authors explore the effects of the pandemic on blood collection in Turkey and illustrate the changes in efficiency throughout a distinct period that incorporates the pandemic. The study would provide a guide for blood bank managers to improve the performance of their organizations.

çalışmada kamu kurumlarındaki stratejik yönetim çalışmalarının örgüt içindeki güç örüntüsünü hangi güç alanları ve kaynakları üzerinden şekillendirdiği sorusuna cevap aranmaktadır.

Purpose The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design. Design/methodology/approach The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies. Findings The results of the study present the researchers’ tendencies and preferences when designing their BSC network models. Research limitations/implications The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs. Originality/value The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.

The COVID-19 pandemic has spread rapidly and affected the whole world. During the process of combating the pandemic, it has become apparent that some physical infrastructures such as intensive care units have been insufficient to meet the current demand. The aim of this study is to select the optimal location for a pandemic hospital and determine the critical factors affecting the selection. The Analytical Hierarchy Process approach is implemented in the study with 27 criteria used to evaluate the alternatives. The data of the study are collected from 23 experts. The result of the analysis proposes the optimal location to establish a pandemic hospital. In addition, the three most important criteria that affect the location selection of the pandemic hospital are Risk, Accessibility, and Opportunities and threats, respectively. Moreover, the results of the sensitivity analysis show that the outputs of the proposed model are robust. A location selection problem for a pandemic hospital was addressed and the factors affecting the location selection are discussed in this study. The proposed model is expected to be a guide for health policymakers, healthcare managers, and public and private investment decision-makers as a decision support system.

<p style='text-indent:20px;'>In the paper, a novel mathematical model for blood supply chain network and a variant of Genetic Algorithm for the problem are proposed. The proposed mathematical model is developed using Mixed-integer nonlinear programming. The model is designed as a location, allocation, and routing problem that includes determining locations of local blood centers, assigning transfusion and blood donation centers to predetermined local blood centers, and routing between them. Eventually, a case study is conducted in the Eastern Black Sea Region of Turkish Red Crescent to illustrate the practicality and validity of the proposed model.</p>