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This paper investigates the overall system risk for a foodgrains supply chain capturing the interrelationship among the risk factors and the effect of risk mitigation strategies.

This paper first calculates the weight of risk factors using an integrated approach of failure mode, effects analysis and fuzzy VIKOR technique. Next, the weights are utilized as input for the weighted fuzzy Petri-net (WFPN) approach to calculate the system risk.

Two different WFPN models are developed based on the relationships among the risk factors, and both models demonstrate a higher risk value for the overall system.

The proposed methodology will help practitioners or managers understand the complexity involved in the system by capturing the interrelationship behaviour. This study also considers the concurrent effect of risk mitigation strategies for calculating the overall system risk, which helps to improve the system’s performance.

This paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.

This paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.

The findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.

The outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.

Specifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

Building a quality teaching force depends fundamentally upon attracting suitable candidates into teaching. This translates into transparent and clear policies and procedures for recruitment and transfers. Teacher recruitment and transfer are significant aspects of teacher management in Indian states because of the size and the differences that exist in different locations, in terms of facilities including access to health care services, higher educational institutions, and also transport and mobility. The presence or absence of these facilities and services determine the perceived quality for teachers, especially as it also determines their and the family members’ (including spouse and children) ability to access education, health care, or job market. This makes the recruitment and transfer policy a critical aspect of teacher management that contributes significantly to the motivation and job satisfaction of the teacher. Karnataka was able to make progress on designing and implementing transparent and effective teacher recruitment and transfer policies and move away from a system plagued by the weaknesses exhibited by other states. This chapter undertakes a historical analysis of teacher recruitment and transfers in the state, examines the determinants that led to current policies and an examination of the on-going changes since the policy was first introduced. Using Karnataka’s example, it argues that effective and efficient teacher management systems can lead to better teacher quality.

This chapter is devoted to sustainable human resource management that leads to sustainable competitiveness. It features the ways human resources can be managed to carry out sustainable goals and the impact of sustainability on employees' attitudes and behaviours. The aim of this study is to explore the complex objectives of sustainability and human resource management and empirically investigate the dynamic relationship between human resources in science and technology and sustainable competitiveness in the case of 35 European countries. Our contribution emphasizes this interrelationship and its causality. For this research, we applied a vector auto-regression (VAR) model, and the Granger causality method to examine the relationship between human resources in science and technology and sustainable competitiveness. A panel data included 314 observations between 2012 and 2021. The panel VAR for analysing the impulse response function was enriched with the 5% and 95%, using Monte Carlo simulations. The research results revealed bidirectional causality in the European countries between human resources in science and technology and sustainable competitiveness. Human resources in science and technology trigger sustainable competitiveness and vice versa. As an element of originality, our study demonstrates that human resources in science and technology contribute to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to the development of human resources in science and technology. Thus, the chapter outlines the role of human resources in science and technology with regard to sustainable human resource management (HRM), and how to navigate these objectives so that they can positively influence sustainable competitiveness.

The adoption of electronic health records (EHRs) and digitization of health data over the past decade is ushering in the next generation of digital health tools that leverage artificial intelligence (AI) to improve varied aspects of health system performance. The decade ahead is therefore shaping up to be one in which digital health becomes even more at the forefront of health care delivery – demanding the time, attention, and resources of health care leaders and frontline staff, and becoming inextricably linked with all dimensions of health care delivery. In this chapter, we look back and look ahead. There are substantive lessons learned from the first era of large-scale adoption of enterprise EHRs and ongoing challenges that organizations are wrestling with – particularly related to the tension between standardization and flexibility/customization of EHR systems and the processes they support. Managing this tension during efforts to implement and optimize enterprise systems is perhaps the core challenge of the past decade, and one that has impeded consistent realization of value from initial EHR investments. We describe these challenges, how they manifest, and organizational strategies to address them, with a specific focus on alignment with broader value-based care transformation. We then look ahead to the AI wave – the massive number of applications of AI to health care delivery, the expected benefits, the risks and challenges, and approaches that health systems can consider to realize the benefits while avoiding the risks.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

As an emerging technology, Radio Frequency IDentification (RFID) and blockchain have the potential to disrupt many areas of business and social structure. However, it is loaded with significant technical, social, legal, financial and ethical complications that bring difficulty in its widespread use within the public distribution system (PDS). This research aims to analyze the barriers to integrated RFID and blockchain adoption in developing countries' PDS. Furthermore, this study also aims to validate the proposed framework against the Indian PDS.

The proposed framework consists of 10 potential barriers to integrated RFID and blockchain adoption. To identify the barriers, this study referred to the extant literature followed by consultations with domain experts. This study prepared the DEMATEL-based questionnaires, collected the data from four domain experts and analyzed them using an integrated Grey-DEMATEL approach.

The obtained results provide a precise list of barriers and the correlations among them. From the results, it is concluded that the unavailability of a skilled workforce at affordable cost, lack of knowledge about privacy level and unclear return on investment and benefits are the most critical blockchain adoption barriers in the context of Indian PDS.

This research proposes a framework consisting of 10 integrated RFID and blockchain adoption barriers in relation to Indian PDS. It also proposes a method for analyzing causal interrelationships between the barriers while allowing for data input from domain experts. Consequently, the framework is capable of coping with experts' biases and data scarcity.

This chapter offers novel insights into how global corporations can innovate to tackle the global waste crisis and gain sustainable competitive positions. Using two of the most prominent types of global waste crises – food and plastic wastes – we discuss the dilemma of food and plastic waste, why innovations in global firms are needed to address them, and argue that a different perspective among those firms is needed, one which conceptualizes the development, dissemination and use of innovations in waste management, and one which recognizes that innovations, thus, created contribute to advancing the creation of economic, environmental and social value. We conclude using an overarching conceptual framework that depicts the complexity of the new perspective.

Point-of-care testing (POCT) at the Emergency Department (ED) attains better objectives in patient care while aiming to achieve early diagnosis for faster medical decision-making. This study assesses and compares the benefits of POCT in the ED in Germany and Malta, while considering differences in their health systems.

This chapter utilizes multiple case study approach using Six Sigma. The German case study assesses the use of POCT in acute coronary syndrome patients, compared to the central lab setting. The Maltese case study is a pilot study of the use of medical ultrasonography as a POCT to detect abdominal free fluid in post-blunt trauma.

This study provides clear examples of the effectiveness of POCT in life-threatening conditions, as compared to the use of traditional central lab or the medical imaging department. Therapeutic quality in the ED and patient outcomes directly depend upon turnaround time, particularly for life-threatening conditions. Faster turnaround time not only saves lives but reduces morbidity, which in the long-term is a critical cost driver for hospitals.

The application of Six Sigma and the international comparison of POCT as best practice for life-threatening conditions in the ED.

This study investigates the stability of the “hospital effect” on performance over time by administrative health data as a source of evidence. Using 78,907 heart failure adult records from 117 hospitals in the Lombardy Region (Northern Italy) over three years (2010–2012), we analyzed hospital performance in terms of 30-day mortality and 30-day unplanned readmissions to gather evidence about the stability of the “hospital effect.” Best/worst performers were identified through multi-level models that combine both patient and hospital covariates. Our results confirm that managerial choices affect hospital performance, and that the “hospital effect” is not, contrary to expectations, stable over the short term. Performance improvement/worsening over the three years has been also analyzed.