Other is modified with added information) and 40 participants answered the questionnaire on each web site. Each brand had two web sites (one is with original, the Lightness, and washing method was added on the original web site. To visualize the tactile sensation,Ĭlothing materials of each brand was measured by KES and the values were displayed in bar chart. Web sites (Gap and Anthropology) were selected and 160 female subjects took part in this study. The purpose of this study is to investigate the effect of textile touch visualization on e-commerce web site. The results from these analyses demonstrate the utility of using the core concepts of salience and complexity to predict the likelihood of legislative direction of agency behavior. Specifically, we assess the effects that public salience and technical complexity have on the willingness of elected officials to use legislation to direct the behavior of four federal regulatory agencies from 1949 to 1996. In this article we extend empirical analyses to study under what conditions efforts at political control of the bureaucracy are more or less likely. But while theoretical models derive expectations regarding both the propensity and the effectiveness of efforts at political control, nearly all empirical research has focused on only the latter. Scholars have employed increasingly sophisticated analyses to demonstrate that it is possible, even likely, for elected officials to direct bureaucratic behavior. Questions regarding the political control of administrative agencies have played a major role in reinvigorating the study of bureaucracy. On the other hand, total consumption, total production, and mean temperature of weather impact the results significantly. The sensitivity analysis shows that CDD/HDD temperatures, extreme minimum temperature, and WTI oil prices have an insignificant effect on the results. Although, this model provides a reasonable fit to the given data, it fails to capture the price spikes effectively. The accuracy of the NARX model with 6 neurons was found to be higher than that of the other models. The three-layer NAR model with 6 hidden neurons was found to have the best performance in terms of one month ahead price prediction. The results indicate that, the NAR neural network provides a better fit to the given data as compared to the other proposed models. In this thesis, three different categories of models are examined which are, stochastic differential equations, ARIMA, and autoregressive neural networks. Stochastic differential equation, linear and nonlinear regression, auto regression, and neural networks are the main techniques that have been implemented. Several attempts have been made to model the energy commodity prices over the past few decades. Additionally, consumers are also highly affected by the changes in the price of oil and gas products. Prediction of the natural gas price is imperative to producers, suppliers, traders, market makers, and bankers involved in the natural gas exploration, production transportation, and trading. The findings significantly contribute to the debate on the influence of the value added information on e-vendor’s ability to become more trustworthy which suggests the need for further research to examine the factors of accurate information and web content classification on e-loyalty and e-shopping relationship. Optimization and Brand Equity have a negative effect on e-Trust, and Internet knowledge imposes no influence on one’s trust and consequently e-Shopping. Interestingly, the study findings suggest that Search Engine ![]() Data were gathered by use of both online and offline customers who could be possibly users of well-known and active e-commerce sites in Middle East area and the results largely support the theoretical relationship between web content, brand reputation, To study the main e-commerce factors leading to higher e-trust and consequently amplify e-shopping throughout a survey in Iran and Middle East Countries. Leading users to use the new technology and gaining its benefits such as cost and time reduction has become one of the most critical success factors of e-business in Iran. User's perception of trust developed and maintained in an E-commerce website has a potential to highly impact the firm's emarketing capability to be competitive through its strategic response to customer’s perception of the virtual environment. Situation at the top of this issue between developing countries of the world. Considering highest rates of Internet users in Middle East in Iran, puts the Iranian’s Ecommerce E-Trust is one of the most fundamental factors of E-Commerce growth which is relatively important to consider in developing countries. E-Commerce and E-trust both are two new concepts in developing countries.
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