International Journal of Data Envelopment Analysis
Volume:11 Issue: 1, Feb 2023

Based on evidence of links between health expenditure and healthcare efficiency, this study aims to measure the performance of the health system in terms of macro-efficiency of healthcare expenditures in Iran over the period 2000-2019, and to investigate efficiency drivers. To this end, at the first stage an input oriented data envelopment analysis (DEA) under the assumption of variable return-to-scale is developed to measure health expenditure efficiency scores with the use of historical data during 20 years. We explore the efficiency of health expenditure by estimating the contribution of healthcare spending to life expectancy, infant survival rate, and cause of death. Next, we examine the link between the efficiency and its determinants through Tobit regression analysis. According to DEA results, it is revealed that the efficiency score of 20 years is 0.82 on average and the standard deviation is 0.11. Findings of the Tobit regression indicate per capita GDP and public health expenditure (% of GDP) have significant negative effect, while control of corruption, and population density are found to have a statistically significant and positive effect on the efficiency of healthcare expenditures in Iran (P<0.05). But education is not statistically significant in determining efficiency. Variation in the efficiency during the years suggests significant potential for improvement in population health status given the current level of health resources allocated to the healthcare. Also, positive impact of governance measures on efficiency indicates that management of the resources is important in the healthcare system, especially in the existence of corruption.

The high consumption of energy and the production of greenhouse gases have forced the government to impose restrictions on energy consumption and reduce environmental pollutants in industries. In this research, a model based on Bounded adjusted measure (BAM) and centralized resource allocation is presented, which reduces pollution among all units by solving only one model. The presented model can be useful for pollution control in specific geographical or industrial area where the central manager wants to reduce pollution to a certain level among all units.

The task of forecasting corporate bankruptcy has garnered considerable attention from financial researchers. Given the consequences of a company's financial issues on its stakeholders, devising techniques and models to anticipate bankruptcy and financial instability has always been an appealing field of financial research. Company investors desire the security of their capital and expect a reasonable return commensurate with the risk they undertake. They anticipate being able to predict a company's financial crises ahead of time and safeguard their investment. To meet this need, researchers have conducted extensive research and used various methods and models to evaluate the financial performance of companies and of course predict their bankruptcy, but the point that should be noted is that none of these methods are enough for their own, and they should be used together and of course using the professional judgments of elite experts. Among the methods that have attracted the attention of researchers in the last few years to facilitate the process of financial decisions is the data envelopment analysis method, which of course has had acceptable results. In this research, 52 listed manufacturing companies in the Tehran Stock Exchange were selected considering to available information into three groups: food and pharmaceutical companies, metal, automobile and machinery companies, and chemical and petrochemical companies, out of which, 21 companies (10 bankrupt and 11 healthy) companies were classified in the first group, 18 companies (10 bankrupt and 8 healthy) in the second group and 13 companies in the third group.

Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production functions in microeconomics. Based on this replacement, DEA is a widely used mathematical programming approach for evaluating the relative efficiency of decision-making units (DMUs) in organizations. Evaluating the efficiency of DMUs with two-stage network structures is important in management and control. The resulting two stage DEA model not only provides an overall efficiency score for the entire process, but also yields an efficiency score for each of the individual stages. In this Paper we develop Nash bargaining game model to measure the performance of DMUs that have a two-stage structure. Under Nash bargaining theory, the two stages are viewed as players. It is shown that when only one intermediate measure exists between the two stages, our newly developed Nash bargaining game approach yields the same results as applying the standard DEA approach to each stage separately. With a new breakdown point, the new model is obtained which by providing example, the results of these models are investigated. Among these results can be pointed to the changing efficiency by changing the breakdown point.

One of the most prevalent issues for managers is pricing. Pricing is one of the variables in the marketing mix and this parameter is directly associated with business income and is a fixable variable in the marketing mix. Therefore, management should be so sensitive about this variable because at this time market is in fierce competition. Most pricing studies in marketing assume that there is a stable relationship between a product’s price and its demand.Game theory is one of the methods that can guide the manager to find the best action and reaction as well as the best strategy that could lead to the most beneficial business.In this paper, we apply game-theoretical models (Stackelberg and Bertrand) to study competition and pricing management strategies to obtain optimal pricing strategies for the corresponding price gains under each strategy. We compare and contrast price gains under these two pricing strategies. Our results indicate that the optimal pricing strategy for competitive firms is governed by the Stackelberg model.