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The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).

The current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.

The research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.

The proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.

This research investigates the effect of imposing a tax on sugar-sweetened beverages (SSBs) on the likelihood of purchasing SSBs. We design and test an experimental framework that examines this and the effects of providing an explanation about the presence of an SSB tax and information about the negative health effects of consuming SSBs. Consistent with Elbel, Taksler, Mijanovich, Abrams, and Dixon (2013) and Taylor, Kaplan, Villas-Boas, and Jung (2019), we find that imposing a tax, in addition to increasing the conspicuousness of the tax by explaining the presence of a tax (and in some cases, the negative health effects) reduces the likelihood of purchasing an SSB anywhere from 8.39% to 18.15%. We contribute to the public health and tax policy literature by testing consumer choice in a controlled experimental setting and considering the effect of individual differences on the choice to purchase SSBs. Imposing a tax on SSBs may be an effective tool for decreasing SSB consumption that is made more effective when the tax is conspicuous.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.

To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.

This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.

The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.

A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.

The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.

To run a job guarantee public policy scheme, it is important to know the aspiration level or the reference point of labor, and accordingly, the labor hour and the wage sequence are to be prepared. The existing job guarantee schemes consider the same wage rates for all types of jobs. As a result, it is to identify the reference point. The present work aims to propose a job guarantee scheme where different types of jobs have different wage rates. The paper explains the choice problem between labor and leisure at different wage rates and proposes complete computational tools to be incorporated into the job guarantee schemes. The paper also gives a mechanism to prepare the list of jobs and corresponding wage rates by maintaining a balance between labor and leisure, where productive activities measure labor hours and labor welfare measures leisure hours. Lastly, the paper provides the analytical tools to interpret the ex-post data of the job guarantee public policy schemes.

The paper has been written based on the Coordination Game and its Welfare Implications in the job guarantee public policy schemes.

The present paper gives an initial work to measure the choice between labor and leisure for the different wage rates practically. This will help in getting the equilibrium strategies, namely, the combination of the labor hour and the wage rate between the policymaker and the labor. This method will help to implement the job guarantee schemes. For example, to run successfully the Basic Income policy, the basic income calculation should give due care; otherwise, there will be a downward trend in the basic income and the welfare of labor will be reduced, because the labor would have to supply excess labor to meet the target income.

This paper derives theories and explains how the equilibrium in this coordination game can be achieved. The paper explains how the policy of the job guarantee schemes can be practiced practically. In the MGNREGA scheme, the public institution declares different categories of jobs with different wage rates. The categories have been classified with respect to the hours required to complete the job. Therefore, the public institution declares different lists or a sequence of pairs of labor hours and wage rates. Moreover, the list is stochastic, because the list can be changed by the inclusion of an offer from the market as well. The labor has to select from the list. The challenge on the part of the public institution is to prepare the list in such a way so that the inclusion of the market offers will not distort the equilibrium of the coordination game. An important method has been proposed here to analyze the ex-post data of job offers so that the preparation of the future sequence of the job offers can be prepared with due care. One objective of the policymaker here is to make a list of job offers in such a way so that the labor supply will be converging to a point and that will not deviate if the wage rate increases further. This objective will make a balance of the distribution of funds between the existing registered labor and the new entrants into the job guarantee schemes.