Agent Based Simulation of Street Robbery

Routine activity theory introduced by Cohen& Felson in 1979 states that criminal acts are caused due to the presenceof criminals, vic-timsand the absence of guardians in time and place. As the number of collision of these elements in place and time increases, criminal acts will also increase even if the number of criminals or civilians remains the same within the vicinity of a city. Street robbery is a typical example of routine ac-tivity theory and the occurrence of which can be predicted using routine activity theory. Agent-based models allow simulation of diversity among individuals. Therefore agent based simulation of street robbery can be used to visualize how chronological aspects of human activity influence the incidence of street robbery.The conceptual model identifies three classes of people-criminals, civilians and police with certain activity areas for each. Police exist only as agents of formal guardianship. Criminals with a tendency for crime will be in the search for their victims. Civilians without criminal tendencycan be either victims or guardians. In addition to criminal tendency, each civilian in the model has a unique set of characteristicslike wealth, employment status, ability for guardianship etc. These agents are subjected to random walk through a street environment guided by a Q –learning module and the possible outcomes are analyzed

Buyer information and brand Choice behavior in markets with asymmetries

This thesis Entitled Buyer information and brand choice behaviour in markets with asymmetries.The period of transition set in by globalization and liberalization has ensued a onsiderable degree of homogeneity with western societies with respect to quantity and quality of goods and services.The study is aimed at finding out how the buyers adapt to the prevalent complex and dynamic market configuration by taking an archetypical situation of information gathering and brand- choice decision of select household consumer durables.The study was based on a set of 301 sample respondents who were either first time purchasers or repeat purchasers for household use, of the items under study in the sample area comprising of rural, urban and semi-urban areas. Data were collected using interview schedule and analysis of the same was done with standard statistical computer programs.Buyer confidence as perceived by buyers with respect to information acquisition and brand-choice represents the felt competence to effectively function in the market.In general, lower levels of education, income and occupation showed lower levels of search. The oldest were also low searchers. The repeat purchasers of the product searched less than the first purchasers. The most important source of information was word of mouth or information from others followed by television advertisements. The least important source of information was billboards, displays and similar forms of advertisements.The second factor is characterized by items representing ‘social attributes’ like, use by many others, use by peers, recommendation by significant others and reputation of the brand. The third factor represents ‘susceptibility to incentives and promotions’.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.