In recent times, the increasing healthcare spending due to the rising health awareness signifies the importance of identifying the appropriate factors that influence patient satisfaction, weight assignment to these factors, and measurement of patient satisfaction becomes important. However, devising a robust objective weighting method for weight assignment of the factors and an analytical method for determining patient satisfaction scores has not been paid enough attention. Motivated by these issues, this work focuses on devising a robust objective weighting method for weight assignment of the factors that influence patient satisfaction, an analytical method for determining patient satisfaction, and real‐life implementation. We first propose a joint weighting methodology to allocate the weights to the factors by integrating the weights determined by different objective weighting methods, namely, mean weight, SD, entropy, criteria importance through intercriteria correlation, and preference selection index‐based approaches. Next, using the weights of these factors, we design a modified weighted aggregated sum product assessment method to determine a single patient satisfaction score by integrating the scores obtained from the weighted sum model and the weighted product model. The proposed methodology is applied to a real‐world dataset provided by a large healthcare provider and diagnostic clinic in Kolkata, India, to exhibit the real‐life implementation. The theoretical insights obtained through non‐parametric tests highlight the significant difference between joint weighting‐based and single weighting‐based methods. The context‐specific insights signify that the patients suffering from arthritis and hyperlipidaemia exhibit lower satisfaction. Also, the patients suffering from dengue express lower satisfaction than the patients suffering from malaria. Additionally, the healthcare provider should focus on improving the service quality of the departments such as ophthalmology, ENT, and dietician.

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Radio frequency identification (RFID) technology is a wireless communication technology that facilitates automatic identification and data capture without human intervention. Since 2000s, RFID applications in the health care industry are increasing. RFID has brought many improvements in areas like patient care, patient safety, equipment tracking, resource utilization, processing time reduction and so on. On the other hand, often deployment of RFID is questioned on the issues like high capital investment, technological complexity, and privacy concerns. Exploration of existing literature indicates the presence of works on the topics like asset management, patient management, staff management, institutional advantages, and organizational issues. However, most of the works are focused on a particular issue. Still now, scholarly attempts to integrate all the facades of RFID-enabled healthcare are limited. In this paper, we propose a conceptual framework that represents the scope for implementation of this technology and the various dimensions of RFID-enabled healthcare and demonstrate them in detail. Also, we have discussed the critical issues that can prove to be potential IJM&P

In 2020, the COVD-19 pandemic emerged as the most severe crisis of the century. Several vaccine manufacturing firms have taken the necessary initiatives to combat this problem. However, profitability issues can bring down these firms’ vaccine manufacturing efforts, thus leading to lower vaccination coverage. Motivated by this issue, we depict a private COVID-19 vaccine supply chain with a supply chain framework comprising of one vaccine manufacturer and multiple private hospitals under demand uncertainty. We incorporate a Stackelberg game-theoretic approach to demonstrate the collaboration between the vaccine manufacturer and the private hospital using wholesale price, two-part tariff and revenue sharing contracts. We determine the optimal number of vaccines and coordination criteria for each contract. Using a real-life approximation of Indian data, we conduct several numerical studies and facilitate the visual depiction of all the theoretical insights obtained from the model. We also discuss the managerial implications of this study. As per our analysis, when private hospitals procure a higher number of vaccines from the vaccine manufacturer, the two-part tariff contract-based collaboration mechanism yields a win-win situation for both the private hospitals and the vaccine manufacturer and is better than the wholesale price contract.

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