This study investigates the effect of changes in corporate payout policy on stock pricesto explore their information content. We nd that positive abnormal returns after dividend increaseannouncements are consistent with the market timing hypothesis and ones after share buybackannouncements are consistent with both the signaling hypothesis and the free cash ow hypothesis.Furthermore, both analyst recommendations and the tone of news articles on announcing rmsare also consistent with these hypotheses. Our results suggest that post-announcement abnormalreturns are attributable to market frictions, namely information asymmetry and agency problems between managers and investors.

In the retail industry, It become more important that what value supply to own customers through service to maintain or increase their customer's purchase. This study builds agent-based model for analyzing what kind of management strategies retailers should employ so that maintain or increase their customer's purchase. Two kinds of agents exist in the proposed model, retailer agents and consumer agents. The retailer agents, on the one hand, vary the provide service based on their own strategies to acquire more customers. The customer agents, on the other hand, they have different preference to service each other, and purchase intention is determined by their satisfaction that is difference perception value and expectation.

Two-sided markets can be found in many industries such as online consumer markets.The markets are economic platforms having two user groups of providers and consumers withnetwork bene ts. The platforms are in the face of erce competition to provide attractive services,prices, supplies. The two-sided markets have been researched using mathematical economics modelsrecent years. The model, however, can only deal with one or two players on a market, thereforeit has limitations to analyse more various players. On the other hand, many research projects ofdynamic pricing and incentive mechanisms have been carried out on power markets. Some of thestudies use agent-based modelling to analyse them as autonomous agents and optimised decisionmaking algorithms. These studies have shown interesting results, but they also have limitationsto analyse further more complex markets and decision making processes of market players takingmanaging conditions into consideration. In this study, we adopt Agent-based gaming to analysethem on a two-sided power market.

This paper attempts to clarify the critical factors that determine the phase transition dynamics occurring in social contagion by an agent-based inverse simulation equipped with genetic algorithm. Previous studies have already shown that structural features such as network structure or social norm, affect significantly the macroscopic dynamics of complex social phenomena. We still need, however, a quantitative analysis of the decisive factors which could yield some particular phase transition in a society, e.g. the emergence of an epidemic. Thus we explore, by utilizing genetic algorithm, the vast parameter space of an agent-based model that represents social contagion, so that we might identify the specific values of parameters resulting in phase transitions. With the results, we will seek to describe their implications for preventing the contagion.

We organized an experiment to show that survey participants take part more when the questionnaires started with less aggressive questions. In our earlier work, we used Bayesian probability and graph algorithms to find relative values of each personal attribute. Using that valuation, we created two sets of the questionnaire each differs in question order and ask 33 personal attributes from participants. The first set of the questionnaire ordered from personal attributes with high valuations such as passport number, driving license number, last name, and monthly income to personal attributes with low valuations such as nationality, gender and office country. On the other hand, the second set of questionnaire ordered from those with low valuations to those with higher valuations. As a result, the number of participants who received the second set of the questionnaire and agrees to submit some information is 70% more than those who received the first set of the questionnaire. Moreover, the second set of participants spend much less time in filling the questionnaire but provides 2.7% more information on average.

This paper presents a power monitoring system to provide the information of the electricity used in the racks of data center. Our Idea to implement a context of power monitoring system is how to deliver the current electricity used and the excess power of the electricity used of a rack and its cost in data center to the data center corporation and to the customers. We implement the system that retrieves data periodically every one second for real time monitoring and one minute interval for system requirement, The one second interval only aimed to be presented in the web and will not be saved in the database but the one minute interval will be saved to be processed further. After retrieving one minute interval data, we process it to be presented into periodically graphs and process it data to get excess power from the contract agreement. We perform our proposed system to fulfill the request from XL Data Center to support fair operation of the data center