Quality Differentiation Under Mixed Competition in Hospital Markets

We use a Hotelling-type model of two hospitals, one for-profit (FP) and the other not-for-profit (NFP) using quality to compete for patients. In an equilibrium that constrains the NFP to zero profits, the NFP share of the market decreases as fixed costs or patient’s marginal utility of quality increase, or as transportation and marginal quality costs decrease, conditions that make quality a more effective tool for attracting patients, improving the ability of the FP to compete for market share. We show that an NFP hospital cannot take the entire market without significant fundraising ability. The market shares predicted by our model are consistent with what is presently observed in Europe and the US.     

SCAD‐penalized quantile regression for high‐dimensional data analysis and variable selection

The present penalized quantile variable selection methods are only applicable to finite number of predictors or do not have oracle property associated with estimator. This technique is considered as an alternative to ordinary least squares regression in case of the outliers and the heavy‐tailed errors existing in linear models. The variable selection through quantile regression with diverging number of parameters is investigated in this paper. The convergence rate of estimator with smoothly clipped absolute deviation penalty function is also studied. Moreover, the oracle property with proper selection of tuning parameter for quantile regression under certain regularity conditions is also established. In addition, the rank correlation screening method is used to accommodate ultra‐high dimensional data settings. Monte Carlo simulations demonstrate finite performance of the proposed estimator. The results of real data reveal that this approach provides substantially more information as compared with ordinary least squares, conventional quantile regression, and quantile lasso.     

Coordination of efforts in disaster relief supply chains: the moderating role of resource scarcity and redundancy

Connecting to the ongoing conversation on the importance of effective coordination, in this paper, we empirically examine the impact of key theoretical modes of coordination, i.e. resource sharing, standardisation of operations, and synchronisation in disaster relief supply chains, on the performance of the humanitarian organisations. Survey data are collected from 101 humanitarian organisations in the emerging countries within Southeast Asia. Data are used to test a conceptually developed model, using structural equation modelling–partial least square (SEM-PLS) approach. The results reveal the significant impact of resource sharing and standardisation on performance outcomes in terms of resources used, responsiveness, and flexibility, while resource sharing is highly weakened by resource scarcity and redundancy. The managerial implication and recommendations are concluded for further research.     

Sustainable agricultural intensification practices and cost efficiency in smallholder maize farms: Evidence from Ethiopia

Sustainable agricultural intensification (SAI) practices have been promoted in developing countries to improve farm productivity and environmental services. However, it is still unclear whether use of a combination of SAI practices has a significant influence on the cost efficiency of smallholder farms. This study investigates whether the cost efficiency of smallholder maize producers in Ethiopia depends on use of input-augmenting and agronomic SAI practices. Stochastic cost frontier models that account for heterogeneity across farms are used for estimation. We find that the use of individual SAI practices increases cost while the combined use of the practices reduces it. The marginal effect on cost reduction is substantial when SAI practices are set at their sample maximum levels. Overall, the results demonstrate the benefit of using a combination of SAI practices in minimizing production cost while addressing the adverse effects of soil degradation and climate variability. To enhance food security, smallholder farm incomes and the sustainability of production in developing countries, policy programs should focus on promoting packages of input-augmenting and agronomic SAI practices.     

The Effect of Investor Sentiment on Nonprofit Donations

Journal of Business Ethics - Prior work shows that capital market participants including investors, analysts, and managers are all impacted by the prevailing level of investor sentiment. We extend...     

The value and consequences of using public health technology assessments for private payer decision-making in Canada: one size does not fit all

Background: Both public and private insurers provide drug coverage in Canada. All payers are under pressure to contain costs. It has recently been proposed that private plans leverage the public health technology assessment (HTA) evaluation process in their decision-making.

Objectives: The objectives of the current study were to examine use of public health technology assessments (HTAs) for private payer decision-making in the literature, to gather the perspectives of experts from both public and private insurers on this practice, and to summarize which value parameters of public evaluations can be used for private payer decision-making.

Methods: A targeted literature review was conducted to identify publications on the use of public HTA or cost-effectiveness data for private payer decision-making on pharmaceutical reimbursement. Concurrently, a roundtable meeting was organized with invited panelists, including private payer representatives and health economic consultants (total n?=?9). The findings from both were synthesized and expressed in qualitative terms using the PICO framework.

Results: The targeted review identified 20 studies meeting the inclusion criteria, primarily originating from the US and Canada. The panelists felt that, despite some similarities, there were substantial differences between both systems. The PICO framework highlighted the issues with transferability between the two systems. Most of the value parameters were either not applicable, needed to be added, needed to be adjusted, or their applicability to private payer systems needed to be confirmed.

Conclusion: Some components of public HTA may be relevant for private payers, however there are reservations that still exist on whether the HTA process in Canada, designed for a public system, can address the informational needs of private payers. Private insurers need to use caution in assessing which value parameters from public HTAs can be used and which need to be confirmed, ignored, enhanced, or adjusted. One size HTA does not fit all applications.     

Measuring technical efficiency of dairy farms with imprecise data: a fuzzy data envelopment analysis approach

This article integrates fuzzy set theory in the data envelopment analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in conventional DEA is that input and output data are measured with precision. However, production agriculture takes place in an uncertain environment, and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data are known to lie within specified intervals and empirically illustrate this approach using a group of 29 dairy producers in Pennsylvania. Compared to the conventional DEA scores that are point estimates, the computed fuzzy efficiency scores are interval bound allowing the decision maker to trace the performance of a decision‐making unit at different possibility levels.     

The Time Cost of Documents to Trade

The article shows that the number of documents required to export and import tend to increase the time cost of shipments. However, the increase in the time cost of increased documentation is much larger for countries that are relatively poor and large in size. One interpretation here is that the relatively rich countries that have more resources and the relatively small countries that rely more on trade invest more in building efficient documentation systems. Our findings suggest caution in interpreting how input-based measures, such as the number of required documents to trade, affect outcome measures.