دانلود رایگان مقاله انگلیسی سیستم هوشمند تجارت الکترونیک B2C برای مهندسی فرایند انجام سفارش الکترونیکی - الزویر 2018

ABSTRACT

In today’s world of digitization, the rise of the e-commerce business around the globe has brought a tremendous change not only in our purchasing habits, but also to the entire retail and logistics industry. Given the irregular e-commerce order arrival patterns, limited time for order processing in e-fulfilment centers, and the guaranteed delivery schedules offered by e-retailers, such as same-day or next-day delivery upon placing an order, logistics service providers (LSPs) must be extremely efficient in handling outsourced e-commerce logistics orders. Without re-engineering the order fulfilment processes, the LSPs are found to have difficulties in executing the order fulfilment process due to the tight handling requirements. This, in turn, delays the subsequent processes in the supply chain, such as last-mile delivery operations, consequently affecting customer satisfaction towards both the retailer and the LSP. In view of the need to improve the efficiency in handling e-commerce orders, this study aims at re-engineering the fulfilment process of e-commerce orders in distribution centers. The concept of warehouse postponement is embedded into a new cloud-based e-order fulfilment preprocessing system (CEPS), by incorporating the genetic algorithm (GA) approach for e-commerce order grouping decision support and a rule-based inference engine for generating operating guidelines and suggesting the use of appropriate handling equipment. Through a case study conducted in a logistics company, the CEPS provides order handling solutions for processing e-commerce logistics orders very efficiently, with a significant reduction in order processing time and traveling distance. In turn, improved operating efficiency in e-commerce order handling allows LSPs to better align strategically with online retailers, who provide customers with aggressive, guaranteed delivery dates.

6. CONCLUSIVE REMARKS AND FUTURE WORK

The capability of logistics service providers in e-order fulfilment is one of the key factors affecting the growth of the online retail business. This paper develops a cloud-based e-order fulfilment pre-processing system, which integrates the genetic algorithm technique and the rule-based inference engine, so that logistics service providers are able to effectively plan for the upcoming internal processing operations of received orders before actual process execution. By so doing, any warehouse postponement strategy can be realized and supported by the proposed system, as presented in this paper. Through consolidating pending e-orders using a cloud database, justifying an optimal internal order processing plan by the genetic algorithm approach, and providing essential operating guidance through the rule-based inference engine for order processing execution, logistics service providers no longer have to process discrete e-orders immediately after they are received. The e-commerce internal order processing flow is therefore streamlined and re-designed. The improved e-order handling capability of logistics service providers eventually reduces the processing time in e-fulfilment centers, thereby meeting the ever tighter delivery requirements of online customers. Ultimately, the intelligent system presented in this paper contributes to the development of the e-commerce business environment from the perspective of the interconnected parties. Logistics service providers become more capable in capturing the logistics of the e-commerce business; retailers can build brand images and loyalty by satisfying the consumers’ needs and expectations, especially considering the timeliness of the last-mile e-order delivery, one of the most critical e-fulfilment processes; and end consumers can receive their purchased items without a long waiting time.