Search results for: insurance pricing

Authors: Chenhong Peng

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Beijing, the capital city of China, is running out of water. The water resource per capita in Beijing is only 106 cubic meter, accounts for 5% of the country’s average level and less than 2% of the world average level. The tension between water supply and demand is extremely serious. For one hand, the surface and ground water have been over-exploited during the last decades; for the other hand, water demand keep increasing as the result of population and economic growth. There is a massive gap between water supply and demand. This paper will focus on addressing the water shortage in Beijing city by increasing water use efficiency in domestic sector. First, we will emphasize on the changing structure of water supply and demand in Beijing under the economic development and restructure during the last decade. Second, by analyzing the water use efficiency in agriculture, industry and domestic sectors in Beijing, we identify that the key determinant for addressing the water crisis is to increase the water use efficiency in domestic sector. Third, this article will explore the two primary causes for the water use inefficiency in Beijing: The ineffective water pricing policy and the poor water education and communication policy. Finally, policy recommendation will offered to improve the water use efficiency in domestic sector by making and implementing an effective water pricing policy and people-engaged water education and communication policy.

Keywords: Beijing, water use efficiency, domestic sector, water pricing policy, water education policy

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Authors: Saleh Alzahrani, Halim Boussabaine

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The majority of Public Private Partnership (PPP) are developed based on the rationale that the design, construction, operation, and financing of a public project is to be awarded to a private party within a single contractual framework. PPP project risks normally include the development and construction of a new asset as well as its operation for decades. Undoubtedly the most serious consequences of risks during the construction period are price and time overruns. These events are amongst the most broadly used scenarios in value for money analysis risks. The sources of risk change over the life cycle of a PPP project. In traditional procurement, the public sector normally has to cover all price distress from these risks. At least there is plenty evidence to suggest that price distress is a norm in some of the projects that are delivered under traditional procurement. This paper will find the impact of construction risk factors into actual construction price into PPP projects. The paper will present a brief literature review on PPP risk pricing strategies, and then using system dynamics (SD) to analyses of the risks associated with the estimated project price. Based on the finding from these analyses a risk pricing association model is presented and discussed. The paper concludes with thoughts for future research.

Keywords: Public Private Partnership (PPP), Risk, Risk Pricing, System Dynamics (SD), construction price

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Authors: Manas Shah

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

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Authors: Brent McKenzie, Victoria Taylor

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The use of QR (Quick Response Codes) codes for customer scanning with mobile phones is a rapidly growing trend. The QR code can provide the consumer with product information, user guides, product use, competitive pricing, etc. One sector for QR use has been in retail, through the use of Electronic Shelf Labeling (henceforth, ESL). In Europe, the use of ESL for pricing has been in practice for a number of years but continues to lag in acceptance in North America. Stated concerns include costs as a key constraint, but there is also evidence that consumer acceptance represents a limitation as well. The purpose of this study is to present the findings of a consumer based study to gage the impact on their use in the retail food sector.

Keywords: electronic price labels, consumer behaviour, grocery shopping, mixed methods research

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Authors: Nesrine Bouzaher, Okba Necira

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The financial aspect of the Algerian economy is part of all sectors that have undergone great changes these two last decades; the goal is to enable economic mechanisms for real growth. Insurance is an indispensable tool for stabilizing these mechanisms. Therefore the national economy needs to develop the insurance market in order to support the investments, externally and internally; it turns out that reinsurance is one of the area which could prove their performance in several markets mainly emerging ones. The expansion of reinsurance in the domestic market is the preoccupation of this work, focusing on factors that could enhance the demand of reinsurance in the Algerian market. This work will be based on an analytical research of the economic contribution of the reinsurance and it’s collusion with insurance; market, then it will be necessary to provide an overview of the product in the national emerging market, finally we will try to investigate on the factors that could enhance the demand in the national reinsurance market so as to determine the potential of Algeria in this area.

Keywords: Algerian reinsurance data, demand trend of Algerian reinsurance, reinsurance, reinsurance market

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Authors: Samipraj Mishra

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Despite the successful implementation of community forestry program, a number of pros and cons have been raised on Terai community forestry in the case of lowland locally called Terai region of Nepal, which is climatically belongs to tropical humid and possessed high quality forests in terms of ecology and economy. The study aims to investigate the local pricing strategy of forest products and its impacts on equitable forest benefit sharing, collection of community fund and carrying out livelihood improvement activities. The study was carried out on six community forests revealed that local people have substantially benefited from the community forests. However, being the region is heterogeneous by socio-economic conditions and forest resources have higher economical potential, the decision of low pricing strategy made by the local people have created inequality problems while sharing the forest benefits, and poorly contributed to community fund collection and consequently carrying out limited activities of livelihood improvement. The paper argued that the decision of low pricing strategy of forest products is counter-productive to promote the equitable benefit sharing in the areas of heterogeneous socio-economic conditions with high value forests. The low pricing strategy has been increasing accessibility of better off households at higher rate than poor; as such households always have higher affording capacity. It is also defective to increase the community fund and carry out activities of livelihood improvement effectively. The study concluded that unilateral decentralized forest policy and decision-making autonomy to the local people seems questionable unless their decision-making capacities are enriched sufficiently. Therefore, it is recommended that empowerment of decision-making capacity of local people and their respective institutions together with policy and program formulation are prerequisite for efficient and equitable community forest management and its long-term sustainability.

Keywords: community forest, livelihood, socio-economy, pricing system, Nepal

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Authors: Necira Okba, Nesrine Bouzaher

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The financial aspect of the Algerian economy is part of all sectors that have undergone great changes these two last decades; the goal is to enable economic mechanisms for real growth. Insurance is an indispensable tool for stabilizing these mechanisms. Therefore, the national economy needs to develop the insurance market in order to support the investments, externally and intern ally; it turns out that reinsurance is one of the area which could prove their performance in several markets mainly emerging ones. The expansion of reinsurance in the domestic market is the preoccupation of this work, focusing on factors that could enhance the demand of reinsurance in the Algerian market. This work will be based on an analytical research of the economic contribution of the reinsurance and it’s collusion with insurance market, then it will be necessary to provide an overview of the product in the national emerging market, finally we will try to investigate on the factors that could enhance the demand in the national reinsurance market so as to determine the potential of Algeria in this area.

Keywords: Algerian reinsurance data, demand trend of Algerian reinsurance, reinsurance, reinsurance market

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Authors: Laxuman Thakuri

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Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

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Authors: Pratheeba Subramanian, Anjula Gurtoo, Mary Mathew

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Transaction of patents in emerging patent markets is gaining momentum. Pricing patents for a transaction say patent sale remains a challenge. Patents vary in their pricing with some patents fetching higher prices than others. Sale of patents in portfolios further complicates pricing with multiple patents playing a role in pricing a bundle. In this paper, a set of 138 US patents sold individually as single invention lots and 462 US patents sold in bundles of 120 portfolios are investigated to understand the dynamics of selling prices of singletons and portfolios and their determinants. Firstly, price variations when patents are sold individually as singletons and portfolios are studied. Multivariate statistical techniques are used for analysis both at the lot level as well as at the individual patent level. The results show portfolios fetching higher prices than singletons at the lot level. However, at the individual patent level singletons show higher prices than per patent price of individual patent members within the portfolio. Secondly, to understand the price determinants, the effect of patent, seller, and bundling related characteristics on selling prices is studied separately for singletons and portfolios. The results show differences in the set of characteristics determining prices of singletons and portfolios. Selling prices of singletons are found to be dependent on the patent related characteristics, unlike portfolios whose prices are found to be dependent on all three aspects – patent, seller, and bundling. The specific patent, seller and bundling characteristics influencing selling price are discussed along with the implications.

Keywords: auction, patents, portfolio bundling, seller type, selling price, singleton

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Authors: Peter J. Robinson, W. J. Wouter Botzen

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Individuals often over-weight low probabilities and under-weight moderate to high probabilities, however very low probabilities are either significantly over-weighted or neglected. Little is known about factors affecting probability weighting in Prospect Theory related to emotions specific to risk (anticipatory and anticipated emotions), the threshold of concern, as well as personality traits like locus of control. This study provides these insights by examining factors that influence probability weighting in the context of flood insurance demand in an economic experiment. In particular, we focus on determinants of flood probability neglect to provide recommendations for improved risk management. In addition, results obtained using real incentives and no performance-based payments are compared in the experiment with high experimental outcomes. Based on data collected from 1’041 Dutch homeowners, we find that: flood probability neglect is related to anticipated regret, worry and the threshold of concern. Moreover, locus of control and regret affect probabilistic pessimism. Nevertheless, we do not observe strong evidence that incentives influence flood probability neglect nor probability weighting. The results show that low, moderate and high flood probabilities are under-weighted, which is related to framing in the flooding context and the degree of realism respondents attach to high probability property damages. We suggest several policies to overcome psychological factors related to under-weighting flood probabilities to improve flood preparations. These include policies that promote better risk communication to enhance insurance decisions for individuals with a high threshold of concern, and education and information provision to change the behaviour of internal locus of control types as well as people who see insurance as an investment. Multi-year flood insurance may also prevent short-sighted behaviour of people who have a tendency to regret paying for insurance. Moreover, bundling low-probability/high-impact risks with more immediate risks may achieve an overall covered risk which is less likely to be judged as falling below thresholds of concern. These measures could aid the development of a flood insurance market in the Netherlands for which we find to be demand.

Keywords: flood insurance demand, prospect theory, risk perceptions, risk preferences

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Authors: Kevin Smith

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Publicly traded company in the US are legally obligated to host earnings calls that discuss their most recent financial reports. During these calls, investors are able to ask these companies questions about these financial reports and on the future direction of the company. This paper examines whether common institutional owners use these calls as a way to indirectly signal to companies in their portfolio to not take actions that could hurt the common owner's interests. This paper uses transcripts taken from the earnings calls of the six largest health insurance companies in the US from 2014 to 2019. This data is analyzed using text analysis and sentiment analysis to look for patterns in the statements made by common owners. The analysis found that common owners where more likely to recommend against direct price competition and instead redirect the insurance companies towards more passive actions, like investing in new technologies. This result indicates a mechanism that common owners use to reduce competition in the health insurance market.

Keywords: common ownership, text analysis, sentiment analysis, machine learning

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Authors: Roengchai Tansuchat, Wassanai Wattanutchariya, Aree Wiboonpongse

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Parboiled rice is one of the most important food grains and classified in cereal and cereal product. In 2015, parboiled rice was traded more than 14.34 % of total rice trade. The major parboiled rice export countries are Thailand and India, while many countries in Africa and the Middle East such as Nigeria, South Africa, United Arab Emirates, and Saudi Arabia, are parboiled rice import countries. In the global rice market, parboiled rice pricing differs from white rice pricing because parboiled rice is semi-processing product, (soaking, steaming and drying) which affects to their color and texture. Therefore, parboiled rice export pricing does not depend only on the trade volume, length of grain, and percentage of broken rice or purity but also depend on their rice seed attributes such as color, whiteness, consistency of color and whiteness, and their texture. In addition, the parboiled rice price may depend on the country of origin, and other attributes, such as certification mark, label, packaging, and sales locations. The objectives of this paper are to study the attributes of parboiled rice sold in different countries and to evaluate the relationship between parboiled rice price in different countries and their attributes by using hedonic pricing model. These results are useful for product development, and marketing strategies development. The 141 samples of parboiled rice were collected from 5 major parboiled rice consumption countries, namely Nigeria, South Africa, Saudi Arabia, United Arab Emirates and Spain. The physicochemical properties and optical properties, namely size and shape of seed, colour (L*, a*, and b*), parboiled rice texture (hardness, adhesiveness, cohesiveness, springiness, gumminess, and chewiness), nutrition (moisture, protein, carbohydrate, fat, and ash), amylose, package, country of origin, label are considered as explanatory variables. The results from parboiled rice analysis revealed that most of samples are classified as long grain and slender. The highest average whiteness value is the parboiled rice sold in South Africa. The amylose value analysis shows that most of parboiled rice is non-glutinous rice, classified in intermediate amylose content range, and the maximum value was found in United Arab Emirates. The hedonic pricing model showed that size and shape are the key factors to determine parboiled rice price statistically significant. In parts of colour, brightness value (L*) and red-green value (a*) are statistically significant, but the yellow-blue value (b*) is insignificant. In addition, the texture attributes that significantly affect to the parboiled rice price are hardness, adhesiveness, cohesiveness, and gumminess. The findings could help both parboiled rice miller, exporter and retailers formulate better production and marketing strategies by focusing on these attributes.

Keywords: hedonic pricing model, optical properties, parboiled rice, physicochemical properties

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Authors: Mirza Waseem Abbas, Abdul Qayyum, Muhammad Islam

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Climate change has emerged as a significant threat to global food security, affecting crop production systems worldwide. This research paper aims to examine the specific impacts of climate change on wheat production in Pakistan, Punjab in particular, a country highly dependent on wheat as a staple food crop. Through a comprehensive review of scientific literature, field observations, and data analysis, this study assesses the key climatic factors influencing wheat cultivation and the subsequent implications for food security in the region. A comparison of two subsequent Wheat seasons in Punjab was examined through climatic conditions, area, yield, and production data. From the analysis, it is observed that despite a decrease in the area under cultivation in the Punjab during the Wheat 2023 season, the production and average yield increased due to favorable weather conditions. These uncertain climatic conditions have a direct impact on crop yields. Last year due to heat waves, Wheat crop in Punjab suffered a significant loss. Through crop insurance, Wheat growers were provided with yield loss protection keeping in view the devastating heat wave and floods last year. Under crop insurance by the Government of the Punjab, 534,587 Wheat growers were insured with a $1.6 million premium subsidy. However, due to better climatic conditions, no loss in the yield was recorded in the insured areas. Crop Insurance is one of the suitable options for policymakers to protect farmers against climatic losses in the future as well.

Keywords: climate change, crop insurance, heatwave, wheat yield punjab

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Authors: Manisha Dubey, Gaurav Gupta, Anoop Arya

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The demand for power supply increases day by day in developing countries like India henceforth demand of reactive power support in the form of ancillary services provider also has been increased. The multi-line and multi-type Flexible alternating current transmission system (FACTS) controllers are playing a vital role to regulate power flow through the transmission line. Unified power flow controller and interline power flow controller can be utilized to control reactive power flow through the transmission line. In a restructured power system, the demand of such controller is being popular due to their inherent capability. The transmission pricing by using reactive power cost allocation through modified matrix methodology has been proposed. The FACTS technologies have quite costly assembly, so it is very useful to apportion the expenses throughout the restructured electricity industry. Therefore, in this work, after embedding the FACTS devices into load flow, the impact on the costs allocated to users in fraction to the transmission framework utilization has been analyzed. From the obtained results, it is clear that the total cost recovery is enhanced towards the Reactive Power flow through the different transmission line for 5 bus test system. The fair pricing policy towards reactive power can be achieved by the proposed method incorporating FACTS controller towards cost recovery of the transmission network.

Keywords: interline power flow controller, transmission pricing, unified power flow controller, cost allocation

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Authors: Jiahau Guo, Yihe Zhang

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This paper proposes solutions for pricing options on stocks paying discrete dividends in markets with daily price limits. We first extend the intraday density function of Guo and Chang (2020) to a multi-day one and use the framework of Haug et al. (2003) to value European options on stocks paying discrete dividends. Next, we adopt the fast Fourier transform (FFT) to derive accurate and efficient formulae for American options and further employ the three-point Richardson extrapolation to accelerate the computation. Finally, the accuracy of our proposed methods is verified by simulations.

Keywords: daily price limit, discrete dividend, early exercise, fast Fourier transform, multi-day density function, Richardson extrapolation

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Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya

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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.

Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa

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Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.

Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

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Authors: Despina Yiakoumi, Agathe Rouaix

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Laboratory experiments were run to investigate the impact of different design characteristics of the auctions, which have been implemented to procure capacity in the UK’s reformed electricity markets. The experiment studies competition among bidders in procurement multi-unit discrete descending clock auctions under different feedback policies and pricing rules. Theory indicates that feedback policy in combination with the two common pricing rules; last-accepted bid (LAB) and first-rejected bid (FRB), could affect significantly the auction outcome. Two information feedback policies regarding the bidding prices of the participants are considered; with feedback and without feedback. With feedback, after each round participants are informed of the number of items still in the auction and without feedback, after each round participants have no information about the aggregate supply. Under LAB, winning bidders receive the amount of the highest successful bid and under the FRB the winning bidders receive the lowest unsuccessful bid. Based on the theoretical predictions of the alternative auction designs, it was decided to run three treatments. First treatment considers LAB with feedback; second treatment studies LAB without feedback; third treatment investigates FRB without feedback. Theoretical predictions of the game showed that under FRB, the alternative feedback policies are indifferent to the auction outcome. Preliminary results indicate that LAB with feedback and FRB without feedback achieve on average higher clearing prices in comparison to the LAB treatment without feedback. However, the clearing prices under LAB with feedback and FRB without feedback are on average lower compared to the theoretical predictions. Although under LAB without feedback theory predicts the clearing price will drop to the competitive equilibrium, experimental results indicate that participants could still engage in cooperative behavior and drive up the price of the auction. It is showed, both theoretically and experimentally, that the pricing rules and the feedback policy, affect the bidding competitiveness of the auction by providing opportunities to participants to engage in cooperative behavior and exercise market power. LAB without feedback seems to be less vulnerable to market power opportunities compared to the alternative auction designs. This could be an argument for the use of LAB pricing rule in combination with limited feedback in the UK capacity market in an attempt to improve affordability for consumers.

Keywords: descending clock auctions, experiments, feedback policy, market design, multi-unit auctions, pricing rules, procurement auctions

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Authors: Akshit Singhal, Xuan Wang, Zhijun Wang, Hao Che, Hong Jiang

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Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity to improve the throughput, reliability and network resource utilization. However, the existing solutions may discourage users to adopt the solutions in the face of multipath scenario where different paths are charged based on different pricing structures, e.g., WiFi vs cellular connections, widely available for mobile phones. In this paper, we propose a Hybrid MPTCP (H-MPTCP) with a built-in mechanism to incentivize users to use multiple paths with different pricing structures. In the meantime, H-MPTCP preserves the nice properties enjoyed by the state-of-the-art MPTCP solutions. Extensive real Linux implementation results verify that H-MPTCP can indeed achieve the design objectives.

Keywords: network, TCP, WiFi, cellular, congestion control

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Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market. By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: precision machinery industry, key success factors (KSFs), key success paths (KSPs), overall profitability, product pricing power, competitive advantages

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Authors: Brenda R. Berca, Jessica S. Vieira, Lucas G. Candido, Matheus C. Ferreira, Paulo S. A. Lopes Filho, Rafaella O. Baracho

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This study aims to estimate the economic value environmental services sustained by Flamboyant Lourival Louza Municipal Park in Goiânia, Goiás, Brazil. The Flamboyant Park is one of the most relevant urban parks, and it is located near a stadium, a shopping center, and two supercenters. In order to define the methods used for the valuation of Flamboyant Park, the first step was carrying out bibliographical research with the view to better understand which method is most feasible to valuate the Park. Thus, the following direct methods were selected: travel cost, hedonic pricing, and contingent valuation. In addition, an indirect method (replacement cost) was applied at Flamboyant Park. The second step was creating and applying two surveys. The first survey aimed at the visitors of the park, addressing socio-economic issues, the use of the Park, as well as its importance and the willingness the visitors, had to pay for its existence. The second survey was destined to the existing trade in the Park, in order to collect data regarding the profits obtained by them. In the end, the characterization of the profile of the visitors and the application of the methods of contingent valuation, travel cost, replacement cost and hedonic pricing were obtained, thus monetarily valuing the various ecosystem services sustained by the park. Some services were not valued due to difficulties encountered during the process.

Keywords: contingent valuation, ecosystem services, economic environmental valuation, hedonic pricing, travel cost

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Dyah Larasati, Karishma Alize Huda, Sri Kusumastuti Rahayu, Martin Daniel Siyaranamual

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Indonesia continues to reform its social protection system to provide the needed protection for its citizen. Indonesia Social Protection consisted of social assistance programs (non-contributory/tax-financed) specifically targeted for the poor and at-risk and social security/insurance program (contributory system). The social assistance programs have mostly been implemented since 1998. The national health insurance has been implemented since 2014 and the employment social insurance since 2015. One major reform implemented has been improving the targeting performance of its major social assistance portfolios including (1) Food Assistance for the poor families (Rastra and BPNT/noncash foods assistance); (2) Education Assistance for poor children; (3) Conditional Cash Transfer for poor families (PKH); and (4) Subsidized beneficiaries of National Health Insurance (JKN-PBI) for the poor and at-risk individuals. For the Social Insurance (through BPJS Employment program), several initiatives have been implemented to expand the program contributing members, although it mostly benefits the formal sector workers. However, major gaps still exist especially for the emerging middle-income groups who typically work at the informal sectors. They have yet to get the protection needed to sustain their social and economic growth. Since 2017, TNP2K (the National Team for Poverty Reduction) under the Vice President office has led the social protection discourse as the government understands the need to address vulnerabilities across the lifecycle and prioritize support to the most at-risk population particularly the elderly, young children and people with disabilities. Discussion and advocacy to recommend for more investment is continuing in order for the government to establish a comprehensive social protection system in the near future (2020-2024) that protects children through an inclusive child benefit program; build a system to benefit more working-age adults (including individuals with disabilities) and a three-tier elderly protection as they reach 65 years.

Keywords: poverty reduction, social assistance, social insurance, social protection

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Authors: Clarinda Vitorino Nhangumbe, Fredericks Ebrahim, Betuel Canhanga

Abstract:

The price of an option weather derivatives can be approximated as a solution of the two-dimensional convection-diffusion dominant partial differential equation derived from the Ornstein-Uhlenbeck process, where one variable represents the weather dynamics and the other variable represent the underlying weather index. With appropriate financial boundary conditions, the solution of the pricing equation is approximated using a nonstandard finite difference method. It is shown that the proposed numerical scheme preserves positivity as well as stability and consistency. In order to illustrate the accuracy of the method, the numerical results are compared with other methods. The model is tested for real weather data.

Keywords: nonstandard finite differences, Ornstein-Uhlenbeck process, partial differential equations approach, weather derivatives

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Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

Abstract:

We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Maryam Ghoreishi, Christian Larsen

Abstract:

In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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Authors: Haluk Eren, Ümit Çelik

Abstract:

Recent developments in unmanned aerial vehicles (UAVs) have begun to attract intense interest. UAVs started to use for many different applications from military to civilian use. Some online retailer and logistics companies are testing the UAV delivery. UAVs have great potentials to reduce cost and time of deliveries and responding to emergencies in a short time. Despite these great positive sides, just a few works have been done for routing of UAVs for package deliveries. As known, transportation of goods from one place to another may have many hazards on delivery route due to falling hazards that can be exemplified as ground objects or air obstacles. This situation refers to wide-range insurance concept. For this reason, deliveries that are made with drones get into the scope of shipping insurance. On the other hand, air traffic was taken into account in the absence of unmanned aerial vehicle. But now, it has been a reality for aerial fields. In this study, the main goal is to conduct risk analysis of package delivery services using drone, based on delivery routes.

Keywords: aerial package delivery, insurance estimation, territory risk map, unmanned aerial vehicle, route risk estimation, drone risk assessment, drone package delivery

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Authors: Pratap Chandra Pati, Prabina Rajib, Parama Barai

Abstract:

The traditional finance theory neglects the role of sentiment factor in asset pricing. However, the behavioral approach to asset-pricing based on noise trader model and limit to arbitrage includes investor sentiment as a priced risk factor in the assist pricing model. Investor sentiment affects stock more that are vulnerable to speculation, hard to value and risky to arbitrage. It includes small stocks, high volatility stocks, growth stocks, distressed stocks, young stocks and non-dividend-paying stocks. Since the introduction of Chicago Board Options Exchange (CBOE) volatility index (VIX) in 1993, it is used as a measure of future volatility in the stock market and also as a measure of investor sentiment. CBOE VIX index, in particular, is often referred to as the ‘investors’ fear gauge’ by public media and prior literature. The upward spikes in the volatility index are associated with bouts of market turmoil and uncertainty. High levels of the volatility index indicate fear, anxiety and pessimistic expectations of investors about the stock market. On the contrary, low levels of the volatility index reflect confident and optimistic attitude of investors. Based on the above discussions, we investigate whether market-wide fear levels measured volatility index is priced factor in the standard asset pricing model for the Indian stock market. First, we investigate the performance and validity of Fama and French three-factor model and Carhart four-factor model in the Indian stock market. Second, we explore whether India volatility index as a proxy for fearful market-based sentiment indicators affect the cross section of stock returns after controlling for well-established risk factors such as market excess return, size, book-to-market, and momentum. Asset pricing tests are performed using monthly data on CNX 500 index constituent stocks listed on the National stock exchange of India Limited (NSE) over the sample period that extends from January 2008 to March 2017. To examine whether India volatility index, as an indicator of fear sentiment, is a priced risk factor, changes in India VIX is included as an explanatory variable in the Fama-French three-factor model as well as Carhart four-factor model. For the empirical testing, we use three different sets of test portfolios used as the dependent variable in the in asset pricing regressions. The first portfolio set is the 4x4 sorts on the size and B/M ratio. The second portfolio set is the 4x4 sort on the size and sensitivity beta of change in IVIX. The third portfolio set is the 2x3x2 independent triple-sorting on size, B/M and sensitivity beta of change in IVIX. We find evidence that size, value and momentum factors continue to exist in Indian stock market. However, VIX index does not constitute a priced risk factor in the cross-section of returns. The inseparability of volatility and jump risk in the VIX is a possible explanation of the current findings in the study.

Keywords: India VIX, Fama-French model, Carhart four-factor model, asset pricing

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