Abstract

Cross-border Ecommerce has developed rapidly in the past three decades. Three phases have been witnessed. The initial phase was a major through telephones and televisions to computer-based ecommerce. The second phase was a relatively quiet period spanning almost a decade in 2000s. Developments during this second phase had confirmed the gradual acceptance of ecommerce in the market, and demonstrated major changes predicted in the first phase. That is the new way for enterprises in supply chains to manage their businesses and consumers to do their shopping in the digital economy. Giant B2B (Business to Business) and B2C (Business to Consumer) ecommerce operators have emerged nationally and internationally. Examples include Amazon, Alibaba and JD.Com. The third phase has been overwhelmed by the rapid explosion of both ecommerce scale and scope in the recent decade. What is astonishing in the third phase is the speed at which Chinese ecommerce businesses have caught up in recent years to become a leading ecommerce market in the world. Record-breaking sensations have been reported with online orders at Double 11 Singles’ Day on 11 November year after year. At the same time, warehousing and logistics management under the e-commerce environment are facing more and more challenges to match the overall market growth rate and customer satisfaction.

This research has aimed itself at capitalizing the benefits of IOT-enabled visibility and traceability technology for adaptive synchronization of pick-and-sort ecommerce order fulfilment. With assistance of IoT systems, the involved men, materials, and machines are turned into smart objects, deploying in the real-time environment. According to the real-time data collected from working stages, an adaptive synchronization mechanism is proposed to balance the picking simultaneity and sorting punctuality. Picking simultaneity attempts to make the items of a pick wave to be picked by smart pickers simultaneously and finished in a same time window, so that the subsequent sorting process could be started as early as possible.

The development of e-commerce has facilitated people’s lifestyles and has also placed higher requirements on the inventory management of e-commerce companies. this research also introduces a new procedure for handling the multicriteria ABC inventory classification problem using stochastic multicriteria acceptability analysis. All possible preferences among the evaluation criteria have been considered. Due to the fact that even under certain preference, it is difficult to reach a group consensus on the exact weight values along with each criterion, we calculate preference-specific intervals under each preference and then formulate a stochastic decision-making problem. To tackle this problem, we consider different distribution functions of the intervals and then compute the holistic acceptability indices to classify stock-keeping units. The results derived from our method are compared to the previous results to show the robustness and superiority of our method.