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Africa has the most deaths from infections yet lacks adequate capacity to engage in vaccine development, production and distribution, the cornerstone of efficiently managing and eliminating several infectious diseases. Research has scarcely explored the role of institutional logics in vaccine development, production and distribution, collectively known as end-to-end vaccine manufacturing. This study aims to explore how institutional logics influence firms to engage in the vaccine manufacturing value chain in Africa.

We conducted multiple case study research using five vaccine manufacturing firms from four African countries in three regions. Qualitative interviews were conducted among 18 executives in 5 vaccine manufacturing firms.

We identified that the state, corporate and market institutional logics disparately influence the different parts of the vaccine manufacturing value chain. These institutional logics co-exist in a constellation that also shapes the organizational forms. Their constellation has dominant logics that guide behavior, while subdominant and subordinate logics influence behavior to a limited extent. The findings show that institutional logics are a function of contextual factors, such as historical events, technological changes and pandemics.

The study developed a typology that identifies vaccine manufacturing firm archetypes, institutional logics and their constellations underpinned by contextual factors. The findings have implications for firms and policymakers, as they may guide the end-to-end vaccine manufacturing interventions adapted for their regions.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

This study aims to reveal how the COVID-19 vaccine was accepted in the Japanese Twitter-sphere. This study explores how the topics related to the vaccine promotion project changed on Twitter and how the topics that were likely to spread changed during the vaccine promotion project.

The computational social science methodology was adopted. This study collected all tweets containing the word “vaccine” using the Twitter API from March to October 2021 and conducted the following analysis: analyzing frequent words and identifying topics likely to spread through the cosine similarity and Tobit model.

First, vaccine hesitancy–related words were frequently mentioned during the vaccine introduction and dissemination periods and had diffusing power only during the former period. Second, vaccine administration–related words were frequently mentioned and diffused through April to May and had diffusing power throughout the period. The background to these findings is that the sentiment of longing for vaccines outweighed that of hesitancy toward vaccines during this period.

This study finds that the timing of the rise in vaccine hesitation sentiment and the timing of the start of vaccine supply were misaligned. This is one of the reasons that Japan, which originally exhibited strong vaccine hesitancy, did not face vaccine hesitancy in the COVID-19 vaccine promotion project.

This study investigated the relationship between last-mile distribution or delivery (LMD) and commodity access through the mediating role of commodity availability and commodity security and the moderating effect of supply chain integration (SCI).

The study adopted the survey research design and employed the questionnaire instrument in collecting primary data from respondents in Eastern Regional Health Institutions in Ghana. The total number of valid responses received was 204. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the relationship between the study variables.

The findings showed that there is a positive and significant relationship between LMD and commodity availability as well as LMD and commodity security. Moreover, while the relationship between commodity availability and commodity access is positive and significant, that between commodity security and commodity access is positive but insignificant. Furthermore, there is a positive and statistically significant relationship between LMD and commodity access. The study discovered that the interaction between LMD and commodity access is insignificant and negatively affected by SCI.

To the best of the authors' knowledge, no previous studies have empirically verified the effect of LMD on commodity access in the presence of mediating factors such as commodity availability and commodity security and SCI as the moderating factors.

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine hesitancy by conducting content analysis and sentiment analysis of the perspectives expressed in comments on videos related to vaccine hesitancy uploaded from India on YouTube.

The assessment of the sentiments of the vaccine-hesitant population is done using Valence Aware Dictionary and sEntiment Reasoner sentiment analysis module implemented with Python’s NLTK library to automatically determine the sentiments of the comments. Manual content analysis was performed on 60.09% viewer comments randomly selected from the total comments in 238 videos on vaccine hesitancy originated from India and labelled each comment with labels “Anti”, “Pro”, “Confused”, “Not Applicable” and “Unrelated” labels.

The study found “Mistrust-Government policies”, “Fear-health related consequences”, “Mistrust-Scientific research”, “Vaccine effectiveness and efficacy” and “Misinformation/myths” as the top five determinants for vaccine hesitancy, whereas “Religious beliefs”, “Fear-Economic consequences”, “Side Effects- short-term” and “Fear-mode of administration” found to be the lesser cited reasons for vaccine hesitancy. However, the study also investigates changes in the inclination of Indian commenters towards vaccine hesitancy and revolving issues over time.

Public health policymakers and health communicators may find the study useful in determining vaccine hesitancy factors in India.

The originality of this study lies in its approach. To date, no sentiment analysis has been conducted on the content released on YouTube by Indian content creators regarding pro- and anti-vaccination videos. This inquiry seeks to fill this research gap.

This study aims to answer the question: What dynamic capabilities do diverse humanitarian organizations have?

We examine this question through the lens of dynamic capabilities with sensing, seizing and reconfiguring capacities. The research team interviewed 15 individuals from 12 humanitarian organizations that had (a) different geographic scopes (global versus local) and (b) different missions (emergency response versus long-term development aid). We also gathered data from secondary sources, including standard operating procedures, company websites, and news databases (Factiva, Reuters and Bloomberg).

The findings identify the operational and dynamic capabilities of global and local humanitarian organizations while distinguishing between their mission to provide long-term development aid or emergency relief. (1) The global organizations, with their beneficiary responsiveness, reconfigured their sensing and seizing capacities throughout the COVID-19 pandemic by pivoting quickly to local procurement or regional supply chains. The long-term development organizations pivoted to multi-year supplier agreements with fixed pricing to counter price uncertainty and accessed social capital with government bodies. In contrast, emergency response organizations developed end-to-end supply chain visibility to sense changes in supply and demand. (2) Local humanitarian organizations developed the capacity to sense demand and supply changes to reconfigure based on their experiential learning working with the local community. The long-term-development local organizations used un-owned and scalable relief infrastructure to seize opportunities to rebuild affected areas. In contrast, emergency response organizations developed their capacity to seize opportunities to provide aid stemming from their decentralized decision-making, a lack of structured procedures, and the authority for increased expenditure.

We propose a theoretical framework to identify humanitarian organizations' operational and dynamic capabilities, distinguishing between global and local organizations and their emergency response and long-term aid missions.

The planning of massive vaccination campaigns often falls to nongovernmental organizations that have to face the critical challenge of vaccinating the largest number of people in the shortest time. This study aims to provide an easy tool for minimizing the duration of mass vaccination campaigns in rural and remote areas of developing countries.

This paper presents a linear mathematical model that combines location, scheduling and routing decisions that allows determining where to locate the vaccination centers, as well as the schedule/route that each medical team must follow to meet the target demand in the shortest time possible. In addition, the paper proposes an heuristic approach that can be integrated in a spreadsheet.

As the numerical experiments show, the proposed heuristic provides good solutions in a short time. Due to its simplicity and flexibility, the proposed approach allows decision-makers to analyze and evaluate several possible scenarios for decision-making by simply playing with input parameters.

The integration of the heuristic approach in a spreadsheet provides a simple and efficient tool to help decision-makers while avoiding the need for large investments in information systems infrastructure by user organizations.

Motivated by a real-life problem and different from previous studies, the objective of the planning is to reduce the length of the vaccination campaigns with the available resources and ensure a target coverage instead of planning for minimizing costs or maximizing coverage. Furthermore, for helping implementation to practitioners, the heuristic can be solved in a spreadsheet.

Several types of vaccines were manufactured by different companies to control and stop the spread of COVID-19. This study aimed to identify the postvaccination side effects of the three different vaccines (Pfizer, AstraZeneca and Sinopharm) among the Iraqi population in Baghdad, Iraq.

A prospective cross-sectional study was conducted in Baghdad, Iraq from May 2021 to March 2022. An online-based questionnaire was used to collect the data through social media, i.e. WhatsApp, Messenger and Google Classroom. A total of 737 vaccinated participants using a snowball sampling methodology were used in this study.

Among the study population, 328 (44.50%) were males and 409 (55.50%) were females. The highest age group that participated was 18–30 years (79.10%) followed by 31–40 years (12.10%), 41–50 years (4.20%), 51–60 years (2.40%) and 60 = years (2.20%). However, 58.8% of the participants received Pfizer-BioNTech, 23.7% received the AstraZeneca-Oxford vaccine and 17.5% received Sinopharm. Out of the total participants, 56.60% showed postvaccination side-effects such as fever, headache, fatigue and dizziness, while 33% showed no side-effects and 10.40% were not sure. Pfizer-BioNTech and AstraZeneca-Oxford vaccines were the most vaccines prevalent of side-effects.

The majority of the side reactions associated with the AstraZeneca and Pfizer vaccines were manageable and self-limiting, including fever, fatigue, headache, joint pain and dizziness, compared to the Sinopharm vaccines, which reported lower postside effects.

During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.

The Indian pharmaceutical industry has contributed significantly to global healthcare by securing superior-quality, inexpensive and reachable medicines worldwide. However, supply chain management (SCM) has been challenging due to constantly shifting requirements for short lifecycles of products, the convergence of industry and changeable realities on the ground. This study aims to identify, assess and prioritize the strengths, weaknesses and opportunities of the pharmaceutical SCM environment in India.

The paper employs a Strength, Weakness, Opportunity, Threat (SWOT) analysis and recognizes strategies to utilize the advantages of the strengths and opportunities, rectify weaknesses and resolve threats.

A variety of strategies that could have a positive effect on the Indian pharmaceutical business are presented. Findings and suggested strategies can significantly advance knowledge, enhance understanding and contribute to the growth of a successful SCM for the Indian pharmaceutical sector.

This paper would act as a roadmap to greater comprehension of the market leaders and market leaders' operating climate. The findings from this study will offer academic scholars and business practitioners deeper insights into the environment of SCM.