Information Acquisition and Price Discrimination

We consider a Hotelling model of price competition where firms may acquire costly information regarding the preferences (i.e. “location”) of customers. By purchasing additional information, a firm has a finer partition regarding customer preferences, and its pricing decisions must be measurable with respect to this partition. If information acquisition decisions are common knowledge at the point where firms compete via prices, we show that a pure strategy subgame perfect equilibrium exists, and that there is “excess information acquisition” from the point of view of the firms. If information acquisition decisions are private information, a pure strategy equilibrium fails to exist. We compute a mixed strategy equilibrium for a range of parameter values.Information Acquisition; Price Discrimination

Information Acquisition and Price Discrimination

We consider a Hotelling model of price competition where firms may acquire costly information regarding the preferences (i.e. “location”) of customers. By purchasing additional information, a firm has a finer partition regarding customer preferences, and its pricing decisions must be measurable with respect to this partition. If information acquisition decisions are common knowledge at the point where firms compete via prices, we show that a pure strategy subgame perfect equilibrium exists, and that there is “excess information acquisition” from the point of view of the firms. If information acquisition decisions are private information, a pure strategy equilibrium fails to exist. We compute a mixed strategy equilibrium for a range of parameter values

Information Acquisition and Price Discrimination

We consider a Hotelling model of price competition where firms may acquire costly information regarding the preferences (i.e. “location”) of customers. By purchasing additional information, a firm has a finer partition regarding customer preferences, and its pricing decisions must be measurable with respect to this partition. If information acquisition decisions are common knowledge at the point where firms compete via prices, we show that a pure strategy subgame perfect equilibrium exists, and that there is “excess information acquisition” from the point of view of the firms. If information acquisition decisions are private information, a pure strategy equilibrium fails to exist. We compute a mixed strategy equilibrium for a range of parameter values

Predicting the competitive position of extended gates: the case of inland customs zones

The extended gate concept aims to reduce the pressure on international ports by postponing administrative processes from these border gates to inland terminals. At present, this approach is used mainly in the container transport industry in European and Asian ports. In this paper we study an extended gate concept, where inland customs services are made available from all entry points of a country. Our aim is to predict the portion of the current flow through border gates that is diverted to these inland customs zones. We propose a time-series gravity models to predict these changes and estimate the parameters of this model using publicly available data for different cargo groups. The focus of our application is Iran, a nation with a large and emerging economy, where goods currently enter through 26 main border gates. In addition to this flow diversion model we explain how flow matrices can be synthesized from the available transport statistics. Our calculations indicate that transportation cost, travel time and customs tariff discounts are the most important for the choice of customs zone. The attractiveness of extended gates increases as the direct cost of transportation between the border gate and destination province rises. Extended customs zones in Iran would have an average share of import flows in 2025 of around 13% and attract a volume of 8.4 million metric tons of goods

Atheism and Prosocial Behavior: Evidence From a Laboratory Experiment

The purpose of this study was to investigate the effect of religion on charitable donation of atheists. We used experimental method utilizing a post-test and a control group. The population of the present study was 314 students at Sharif University of Technology recruited in the second half of 2018 semester and randomly assigned to either the experimental (n=27) or the control (n=26) group. Then subjects answered some demographic questions (i.e., age, gender, and income) and some questions from the NEO Five-Factor Inventory, and were also primed using a research-made Religious Priming Tool. Then they were given an opportunity to donate money to Mahak Charity, while keeping the record of donation amounts. At the end, they reported their religious orientation again and answered questions to check their knowledge of the objectives of the experiment. Finally, we compared the median of the donations in two groups. The data analyzed using the non-parametric Mann-Whitney test due to the abnormality of data distribution. The results showed that highlighting religion had no effect on donation of the atheists. The experiment warrants further research for the purpose of a better understanding of mechanisms influencing prosocial behavior

A review of the structure and dynamics of nanoconfined water and ionic liquids via molecular dynamics simulation

During the past decade, the research on fluids in nanoconfined geometries has received considerable attention as a consequence of their wide applications in different fields. Several nanoconfined systems such as water and ionic liquids, together with an equally impressive array of nanoconfining media such as carbon nanotube, graphene and graphene oxide have received increasingly growing interest in the past years. Water is the first system that has been reviewed in this article, due to its important role in transport phenomena in environmental sciences. Water is often considered as a highly nanoconfined system, due to its reduction to a few layers of water molecules between the extended surface of large macromolecules. The second system discussed here is ionic liquids, which have been widely studied in the modern green chemistry movement. Considering the great importance of ionic liquids in industry, and also their oil/water counterpart, nanoconfined ionic liquid system has become an important area of research with many fascinating applications. Furthermore, the method of molecular dynamics simulation is one of the major tools in the theoretical study of water and ionic liquids in nanoconfinement, which increasingly has been joined with experimental procedures. In this way, the choice of water and ionic liquids in nanoconfinement is justified by applying molecular dynamics simulation approaches in this review article

Fundamentals and Stock Return in Pharmaceutical Companies: a Panel Data Model of Iranian Industry: Hydrogel based tablet for vaginal candidiasis

Stock return is usually considered to be affected by firm’s financial ratios as well as economic variables. Fundamental method assume that stock returns is not solely related to the stock market. Most result come from the company condition, industry situation and whole economy. In this paper, this relationship between stock return and fundamentals is studied using the data for 22 pharmaceutical companies in Tehran Stock Exchange over a 7 year period, and effective factors on stock return are investigated. Because of our data natural we used panel data model from econometric methods.The results show that 80 pecent of change in stock return can be explained with 9 fundamental variables factors including debt-equity ratio, working capital to total asset, current ratio, net profit margin, operating cycle, market share, inflation rate of medicinal products prices, total asset, and exchange rate have significant effect on stock return. This factors can be used in decision making in pharmaceutical industry

Fundamentals and Stock Return in Pharmaceutical Companies: a Panel Data Model of Iranian Industry

Abstract Stock return is usually considered to be affected by firm's financial ratios as well as economic variables. Fundamental method assume that stock returns is not solely related to the stock market. Most result come from the company condition, industry situation and whole economy. In this paper, this relationship between stock return and fundamentals is studied using the data for 22 pharmaceutical companies in Tehran Stock Exchange over a 7 year period, and effective factors on stock return are investigated. Because of our data natural we used panel data model from econometric methods.The results show that 80 pecent of change in stock return can be explained with 9 fundamental variables factors including debt-equity ratio, working capital to total asset, current ratio, net profit margin, operating cycle, market share, inflation rate of medicinal products prices, total asset, and exchange rate have significant effect on stock return. This factors can be used in decision making in pharmaceutical industry

A Four-Stage Algorithm for Community Detection Based on Label Propagation and Game Theory in Social Networks

Over the years, detecting stable communities in a complex network has been a major challenge in network science. The global and local structures help to detect communities from different perspectives. However, previous methods based on them suffer from high complexity and fall into local optimum, respectively. The Four-Stage Algorithm (FSA) is proposed to reduce these issues and to allocate nodes to stable communities. Balancing global and local information, as well as accuracy and time complexity, while ensuring the allocation of nodes to stable communities, are the fundamental goals of this research. The Four-Stage Algorithm (FSA) is described and demonstrated using four real-world data with ground truth and three real networks without ground truth. In addition, it is evaluated with the results of seven community detection methods: Three-stage algorithm (TS), Louvain, Infomap, Fastgreedy, Walktrap, Eigenvector, and Label propagation (LPA). Experimental results on seven real network data sets show the effectiveness of our proposed approach and confirm that it is sufficiently capable of identifying those communities that are more desirable. The experimental results confirm that the proposed method can detect more stable and assured communities. For future work, deep learning methods can also be used to extract semantic content features that are more beneficial to investigating networks