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The vaccine supply chain (VSC) performance remains under stress during pandemic outbreaks than conventional vaccination drives due to desired vaccination coverage. Therefore, it is essential to identify the crucial performance objectives (POs) and their interrelationship structure and prioritize them to improve performance in a pandemic VSC.

This study combines the decision-making trial and evaluation laboratory based analytic network process (DANP) method with spherical fuzzy sets (SFS) to explore critical POs of the pandemic VSC in the balanced scorecard framework. The SFS theory tackles the uncertainty of POs and DANP interlaced causal relationships among crucial POs to the pandemic VSC while ranking them for prioritization.

This work identifies 32 issues associated with pandemic VSC and maps them against 13 POs. Effective communication, adequate health financing and operating cost optimization are the most critical POs, and operational issues listed under them must be prioritized to improve the overall VSC performance for future pandemics. The relationship structure among these POs is also summarized using the balanced scorecard framework in a strategy map.

The strategy map proposed in this study can help practitioners to address the causality among different POs and underlying issues for the sudden expansion of vaccination programs during pandemics from an economic, social and operational perspective.

To the best of the authors’ knowledge, this is the first empirical study to suggest improving the VSC performance during the pandemic by focusing on the causative relationship and priority of different detected POs.

The study aims to develop an integrated quantitative approach and suggest a framework to assess the impact of a technological intervention on the internal process dimension of the vaccine supply chain (VSC) system for multiple administered regions.

An evaluation index system is developed by selecting suitable performance indicators (PIs) that define the objectives of a VSC. Then multicriteria decision-making (MCDM) methods are applied to obtain pre and post-intervention relative ranks for the regions and performance scores of the objectives. A bilateral data envelopment analysis (DEA) compares significant efficiency differences between improvement and deterioration groups.

This study demonstrates that technological intervention improves the internal process dimension of a VSC for the regions under consideration. The empirical study delivers two groups of regions showing improvement or deterioration in relative performance ranking due to the technological intervention. However, the efficiency-based bilateral comparison may reveal an insignificant difference between the two groups.

Decision-makers associated with VSC will find the suggested model helpful in assessing the impact of technological intervention. They can easily identify specific objectives of VSC's internal process dimension, whether a particular region has observed an improvement or deterioration in its relative performance and maximize the outcome by focusing on the areas of concern for a specific region.

This study is the first to provide a quantitative approach that empirically determines relative performance improvement or deterioration of different regions for a set of identified VSC objectives in the context of the Indian states.

This study aims to investigate magnetohydrodynamic (MHD) conjugate pure mixed convection considering interior heat production and resistive heating inside a square closed/open cavity featuring a rotating cylinder for aiding (clockwise) and opposing (counterclockwise) flow configurations. Moreover, the impacts of altering cylinder size and conductivity on the system’s overall performance to determine optimum conditions are examined in this investigation.

The closed chamber is differentially heated by keeping high and low temperatures at the vertical boundaries. In contrast, the open cavity has a heated left wall and an open right boundary. The Galerkin finite element method is used to solve the Navier–Stokes and the thermal energy equations, which construct the present study’s mathematical framework. Numerical simulations are conducted for the specified ranges of several controlling parameters: Reynolds (31.62 ≤ Re ≤ 1000), Grashof (10³ ≤ Gr ≤ 10⁶) and Hartmann numbers (0 ≤ Ha ≤ 31.62), and volumetric heat generation coefficient (Δ = 0, 3).

When Gr, Re and Ha simultaneously increase, the average Nusselt number along the warmed boundary rises accordingly. Conversely, interior heat production lowers heat transmission within the computational domain, which is also monitored regarding mean fluid temperature, overall entropy production and thermal performance criterion. Finally, the open cavity confirms better thermal performance than the closed cavity.

Comprehending the impacts of the magnetic field, Joule heating, internal heat generation and enclosed or open boundary on pure MHD combined free-forced convective flow offers valuable understandings of temperature fluctuations, velocity propagations, heat transport and irretrievable energy loss in numerous engineering applications.