Online Shopping Services Research Articles

Penentuan Jasa Online Shop Menggunakan Metode AHP sebagai Pendukung Keputusan dalam Pembelian

Online Shop is one of the ways people today make sales and purchases transactions to meet the needs of the community. Online shopping is not a taboo subject for today's society, especially people in Indonesia, with a population of 170 million active users of the internet or social media. For data management in this study, researchers will use primary data taken directly through the distribution of the AHP questionnaire. The questionnaire will be distributed to 10 respondents as representatives of the population. The sampling technique used in this research is theTechnique in Purposive Sampling which the distribution of the questionnaire to the respondents has been selected or determined with a specific purpose. Respondents in this study are people who live in Griya Rawa Makmur Bengkulu Housing who have used or have made online purchases on the three applications being studied. This is because to determine the level of value comparison between the quality of online shopping services from three applications, namely: Tokopedia, Shoppe and Lazada.
 Based on the results of calculating the priority weight value for online shop services, the priority weight value for the reliability element is 46.87%, the Responsiveness element is 21.10, the assurance element is 8.58, the empathy element is 14.31%, while for the tangible element it is 9.14%. Based on the results of calculating the total weight value for shope online services, shopee online services are the highest services in demand, this can be seen from the weight value reaching 0.5186 or 51.86%.

Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode

For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers’ experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company’s supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters.