درخت حوزه‌های تخصصی

The world of digital marketing has been fast advancing in recent times. Marketers have developed various practices to attract consumers to their products and services. Online shopping applications have introduced different methods to encourage consumer impulse buying. However, past literature has overlooked the 7C framework, despite its introduction during the early stages of e-commerce development. Thus, this study aims to examine the dimensions of digital marketing and the mediating role of emotions on impulse buying behavior in e-commerce shopping platforms. This study used the Stimulus-Organism-Response (SOR) framework as the underpinning theory for developing the proposed framework. The 7Cs framework, serving as the stimulus (S), includes content, context, commerce, customization, connection, communication, and community. Emotions represent the organism (O), while impulse buying behavior is the response (R). A survey was conducted to collect data from 331 shoppers from two major online platforms in Malaysia. Exploratory Factor Analysis was performed and revealed six dimensions of digital marketing. Furthermore, it was found that emotions partially mediate the relationship of (a) context, (b) connection, and (c) commerce on impulse buying behavior. Emotions fully mediate the relationship between (a) communication and (b) customization on impulse buying behavior. This study enhances the understanding of the 7C framework, which is underexplored in the context of e-commerce. The 7C framework can be used to assess not only website design but also the design of e-commerce shopping platforms.

Fog computing is considered a promising solution to minimize processing and networking demands of the Internet of things (IoT) devices. In this work, a model based on the energy consumption evaluation criteria is provided to address the deployment issue in fog computing. Numerous factors, including processing loads, communication protocols, the distance between each connection of fog nodes, and the amount of traffic that is exchanged, all have an impact on the re-search system's overall energy consumption. The power consumption for implementing each com-ponent on the fog node as well as the power consumption for information exchange between the fog nodes are taken into account when calculating each fog node's energy use. Each fog node's energy consumption is closely correlated to how its resources are used, and as a result, to the average normalized resource utilization of a fog node. When the dependent components are spread across two distinct fog nodes, the transfer energy is taken into account in the computations. The sum of the energy used for transmission and the energy used for computational resources is the entire amount of energy consumed by a fog node. The goal is to reduce the energy consumption of the fog network while deploying components using a novel metaheuristic method.  Therefore, this work presents an enhanced water strider algorithm (EWSA) to address the problem of deploying application components with minimum energy consumption. Simulation experiments with two scenarios have been conducted based on the proposed EWSA algorithm. The results show that the EWSA algorithm achieved better performance with 0.01364 and 0.01004 optimal energy consumption rates.