We investigate people’s attitudes towards the possible use of mobile negotiation support systems (NSS) in different social contexts and the consequences for their design. For that purpose we developed an online survey based on existing models of technology acceptance. In the questionnaire we showed five filmed scenarios of NSS use contexts. The data collected from 120 respondents, showed (a) th...

the electronic industry suffers a rapid changing and highly rival environment. thus, firms have an essential need to strive for acquiring the competitive advantage. strategy organizational agility (soa) is a tool which enables to assist firms to attain the competitive advantage. therefore, this study benchmarks the core competencies from a case study within the supply chain network and establis...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

scientific communications network is presented in, sociology of science. and we can use steven's evaluative bibliometrics to map it. in citation network approach, scientist's communication behavior is predicted through their citation behavior. in this paper, first, concepts such as sociology of science, scientific community, scientific communications and its kinds are described. two k...

in conventional dea models, decision making units (dmus) are generally assumed as a black-box while the performance of decision making sub-units (dmsus) and their importance play crucial roles in  analyzing the performance of systems which have internal processes. the present paper introduces an ideal network which have efficient processes and next purposes a new approach for evaluating importa...

It is well-known that single hidden layer feed-forward neural networks (SLFNs) with at most n hidden neurons can learn n distinct samples with zero error, and the weights connecting the input neurons and the hidden neurons and the hidden node thresholds can be chosen randomly. Namely, for n distinct samples, there exist SLFNs with n hidden neurons that interpolate them. These networks are calle...