This paper assesses why it's important for businesses to make the commitment to engage in an effective e-commerce strategy. In a tough economy like the one we are currently experiencing, engaging in the pursuit of internet sales is a legitimate way for businesses to grow their market share. In the same vain as depicted in the movie Field of Dreams, "if you build it they will come." An online presence in these difficult times will improve a firm's competitive posture, reduce advertising costs, evolve it from a local entity to a global supplier, and protect it against major paradigm shifts. Unlike traditional forms of customer communications, online purchasers have control of the information they want to review. The links these purchasers select give an indication concerning their preferences as they navigate through the website, or the areas where they have difficulty completing a transaction due to a problem. Tracking these preferences and problem areas in information systems is one way to predict issues that consumers in a certain profile group may have. Once the preferences of online customers have been assessed and identified, they have to be incorporated into website design solutions. When implementing their online capabilities, companies must commit to taking an online leadership position, keeping a quality focus on products and the services that deliver them, and tailoring online systems to support collective learning organizations. Implementing high quality websites that support efficient online business transactions requires investment in servers and supporting information technology systems to collect, process, store, and distribute the required supporting customer and transaction data. By committing to invest in IT systems designed to support business strategies targeting leadership positions in key business areas, companies can experience growth even in poor economic conditions. Otherwise, the business will take up the stature of a "follower" and slowly lose ground and market share to competitors.
The continuous creation of data has posed new research challenges due to its complexity, diversity and volume. Consequently, Big Data has increasingly become a fully recognised scientific field. This article provides an overview of the current research efforts in Big Data science, with particular emphasis on its applications, as well as theoretical foundation.
Internet of Things (IoT) refers to the complex systems generated by the interconnections among widely available objects. Such interactions generate large networks, whose complexity needs to be addressed to provide suitable computationally efficient approaches. In this article, we propose a distributed local community detection algorithm based on specific properties of community centre expansions (DLCD-CCE) for large-scale complex networks. The algorithm is evaluated via a prototype system, based on Spark, to verify its accuracy and scalability. The results demonstrate that compared to the typical local community detection algorithms, DLCD-CCE has better accuracy, stability and scalability, and effectively overcomes the problem that existing algorithms are sensitive to the location of initial seeds.
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