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The Internet has become an essential part of day-today business. Many personal and industrial business use cases assume the availability of perpetual Internet access for fulfillment. The access to the Internet, ironically, is expensive, given various tiered pricing models that Internet Service Providers (ISP) employ. In many developing economies, the availability of the Internet is very sporadic,...
In recent years online social network is used as a marketing platform for advertisement industry for advertising their products or services to the huge volume of people in short period of time. In that Information Diffusion is a type of process in social network for predicting the future interest of people for some specific product or services. For example, a people are interested to buy any new product...
The development needs the internet and cable television entertainment increase per year that affect popping up various multimedia service provider company which is offered a lot of services to win the market. This makes customer has a lot of company choices and makes customer to be more demanded and move easily from a provider to other provider, where company knows that keep customer has the cost...
Data analytics is an emerging domain in information systems literature and an increasing number of companies try to use data analytics to make sense out of their environment. Accordingly, the ability of companies to leverage digital data to explore new business opportunities becomes important to develop competitive advantage in digitalized world. Consequently, extant literature investigates different...
Agile development for big data analytics has become the new normal. However, research questions remain: 1) how should a big data system be designed and developed to effectively support advanced analytics? and 2) how should the agile process be adapted for big data analytics development? This article contributes an Architecture-centric Agile Big data Analytics (AABA) development methodology evolved...
Big Data is an emerging research topic. However, the term remains fuzzy and is seen as an umbrella term. Its origin, composition, possible strategies, and outcomes are unclear. This impedes the positioning of publications addressing business administration issues related to Big Data. The missing theoretical foundation of Big Data has been recognized, as has the need for underlying relationships and...
Stock market identification and forecasting are highly complex in terms of mathematical modeling due to the complexity of internal structure and external forces that contributes the nonlinear dynamics of its behaviors. In this paper, fuzzy system is used to identify the stock market and produce the parameters to estimate the closing price of the selected stock market. Due to the abilities of incorporating...
This paper presents the architecture and working principles of a Decision Support System (DSS) for logistics networks. The system relies on a data-driven discrete-event simulation model. A brief introduction to Reinforcement Learning (RL) and an explanation of the adoption of RL to the concepts of the DSS is given. An illustration of the realization is presented using a specific aspect of a logistics...
This paper measures marketing ability and financial performance and examines what cause the overall operations inefficiency based on the operational process decomposition. The empirical research on e-portal and e-commerce company show that e-portal company has better marketing ability while e-commerce firm has better financial performance. For e-commerce company, it is marketing ability conversion...
Consumer-oriented companies can no longer afford to make decisions or measure results based on gut feeling. They must be able to take advantage of all available data. Advanced analytics makes it possible to capture value and benefit from big data, however, this isn't a given. Companies must hire, develop, and retain skilled analysts, who can distinguish relevant from irrelevant data, draw the right...
We propose a novel approach for predicting Web user click intention, using pupil dilation data generated by an eye-tracking device as input. Our goal is to determine if this variable is useful to differentiate choice and no-choice states, and if so, to generate a classification model for predicting choice understood as a click. For this, we performed an experiment with 25 healthy subjects in which...
Small and medium-sized enterprises play a very important role in China's economic and social development. Their development is inseparable from the financial support, and the development of credit business is also an important aspect of bank's operation. At the time of solving the problem of financing difficulties of small and medium-sized enterprises, how to manage credit risk will become an important...
Today's supply chain (SC) is highly complex and inter-connected so disruption at one company can propagate to other companies in an unexpected manner. However, most approaches in the area of risk management provide only static analysis of the SC risk but not the propagation of disruption through the SC network. Thus, in this paper, we propose a time-based model that quantifies the magnitude of the...
This paper describes a decision support system (DSS) built on knowledge extraction using simulation-based optimization and data mining. The paper starts with a requirements analysis based on a survey conducted with a number of industrial companies about their practices of using simulations for decision support. Based upon the analysis, a new, interactive DSS that can fulfill the industrial requirements,...
Simulation-based optimisation is popularly employed to determine the best system configuration of complex simulation models. However, it is assumed that the input distribution and parameters are known. In this paper, the input distribution parameter is assumed to be unknown and the impact of the same on the optimal system configurations obtained is investigated. Bootstrapping of the sample data is...
A novel short-wave passive location algorithm based on radial basis function neural networks (RBFNN) is proposed. Using the RBFNN's characteristic of approximating any continuous nonlinear function, the fusion of electromagnetic spectrum sensing data is realized by sample learning. And the mapping model of short-wave monitoring data, detecting data and targets' position information is constructed...
As Twitter usage increases worldwide, it becomes an important part of the big data ecosystem. People from across the globe tweeting and retweeting a large number of tweets instantaneously results in exponential growth of the information diffusion. This in turn can cause information bubbles. As data from Twitter and other microblogs are used in predictive analytics in many areas such as stock price...
Due to advancement of social network and popularization of mobile devices, the existing relational database management system(RDBMS)'s processing of massive data has become an issue. NoSQL is a database management system which makes processing of massive and/or unstructured data easier, and many companies today tend to start a project using NoSQL. Moreover, converting the RDBMS of current systems...
As ERP was believed to provide a lot promising benefits, many companies try to implement it in their business processes. By implementing ERP, they expect to get those promised benefits. In fact, although many companies have successfully implemented ERP systems, not all companies get the benefits of ERP system since ERP systems have not been able to diffuse in the routine of the organizations. A lot...
Modern organizations face the challenge of constantly evolving skills and an ever-changing demand for products and services. In order to stay relevant in business, they need their workforce to be proficient in the skills that are in demand. This problem is exacerbated for large organizations with a complex workforce. In this paper, we propose a novel, analytics-driven approach to help organizations...
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