Prioritizing the vaccine supply chain issues of developing countries using an integrated ISM-fuzzy ANP framework

An equitable and accessible vaccine supply chain network in the epidemic outbreak of COVID-19 under uncertainty

Vaccination is one of the most efficient ways to restrict and control the spread of epidemic outbreaks such as COVID-19. Due to the limited COVID-19 vaccine supply, an equitable and accessible plan should be prepared to cope with. This research focuses on designing a vaccine supply chain while aiming to achieve an equitable and accessible network. We present a novel mathematical formulation that helps to optimize vaccine distribution to inoculate people with various priority levels to achieve an equitable plan. The transshipment strategy is also incorporated into the model to enhance the accessibility of COVID-19 vaccine types between health facilities. The nature of COVID-19 is dynamic over time due to mutations, and the protection level of each vaccine type against this disease is not exact. Besides, complete information about the demand for different vaccine types is not available. Hence, we use Multi-Stage Stochastic Programming as a reliable strategy that is organized to manage stochastic data in a dynamic environment for the first time in the vaccine supply chain network. The scenarios in this approach are generated using a Monte Carlo simulation method, and then a forward scenario reduction technique is conducted to construct a suitable scenario tree. The practicality and capability of the model are shown in a real-life case of Iran. The results show that the performance of the Multi-Stage Stochastic Programming is significantly improved compared with the two-stage stochastic programming regarding the total cost of the vaccine supply chain and the number of the shortage units.

Modeling the dynamical ethnic processes in multinational society

Purpose

The problem of ethnic conflicts and unrest is at the forefront in a diverse world today. This paper aims to identify ways of resolving social conflicts and establishing a balanced way of taking into account the diverse interests of a multinational society.

Design/methodology/approach

Modeling of dynamical ethnic processes in the Republic of Kazakhstan was based on the Parson's sociological scheme and the Nash equilibrium theory. The model consists of differential equations describing the development of four ethnic subsystems: political system, economic system, societal community and Institute of the Assembly of the People of Kazakhstan. This model allows investigating how the interests of various ethnic groups change over time and identifying the states of equilibrium in which the interests of all groups are satisfied.

Findings

The results of computer simulation showed that one of the solutions to the problem of social stability is establishing social equilibrium. For this, the Institute of the Assembly of the People of Kazakhstan (APK Institute) must take changes that occur within ethnic groups into account. The proposed model can reveal states of equilibrium with respect to positive and negative dynamic processes that exist between different ethnic groups.

Originality/value

The proposed model can be used to predict changes in social behavior and find balance between ethnic subsystems in the research on ethnic processes in multinational countries to early detect conflicts of interest and crisis situations. Future studies will benefit from expanding the range of subsystems that can affect alterations in the ethnic community.

A fuzzy multi-criteria framework to identify barriers and enablers of the next-generation vaccine supply chain

Purpose

Due to the introduction of new vaccines in the child immunization program and inefficient vaccine supply chain (VSC), the universal immunization program (UIP), India is struggling to provide a full schedule of vaccination to the targeted children. In this paper, the authors investigate the critical factors for improving the performance of the existing VSC system by implementing the next-generation vaccine supply chain (NGVSC) in India.

Design/methodology/approach

The authors design a fuzzy multi-criteria framework using a fuzzy analytical hierarchical process (FAHP) and fuzzy multi-objective optimization on the basis of ratio analysis (FMOORA) to identify and analyze the critical barriers and enablers for the implementation of NGVSC. Further, the authors carry out a numerical simulation to validate the model.

Findings

The outcome of the analysis contends that demand forecasting is the topmost supply chain barrier and sustainable financing is the most important/critical enabler to facilitate the implementation of the NGVSC. In addition, the simulation reveals that the results of the study are reliable.

Social implications

The findings of the study can be useful for the child immunization policymakers of India and other developing countries to design appropriate strategies for improving existing VSC performance by implementing the NGVSC.

Originality/value

To the best of the authors’ knowledge, the study is the first empirical study to propose the improvement of VSC performance by designing the NGVSC.

Bullwhip effect reduction map for COVID-19 vaccine supply chain

The growing COVID-19 virus pandemic outbreak causes an urgent need to produce its vaccine. Pharmaceutical companies would encounter a massive wave of unforeseen demand for the COVID-19 Vaccine after the vaccine production that could lead to a bullwhip effect in the COVID-19 Vaccine Supply Chain (CVSC). The main objective of this study is to design a cognitive map based on the influential factors on the Bullwhip Effect Reduction (BER) of CVSC. Hence, in the first step, the affecting factors on the BER of CVSC are identified and ranked based on their importance from the pharmaceutical experts using the AHP technique. In the second step, 13 out of 18 identified factors are considered for further analyzing and understanding their relationship by Fuzzy Cognitive Mapping (FCM) technique. Furthermore, three different forward scenarios and three backward scenarios are carefully constructed to find the optimal solution for BER on pharmaceutical organizations. The obtained results show that the flexibility factor is the starting point of the backward scenario, which reduces the bullwhip effect in CVSC. Beside, by improving the inventory management and reliability factor, it would be effectively possible to control the lead-time factor and consequently, overcome the bullwhip effect in CVSC.